Data from: High-molecular-weight polymers from dietary fiber drive aggregation of particulates in the murine small intestine
Preska Steinberg, Asher1; Datta, Sujit S.2; Naragon, Thomas1; Rolando, Justin C.1; Bogatyrev, Said R.1; Ismagilov, Rustem F.1
- California Institute of Technology
- Princeton University
Published Jan 03, 2020; Updated Feb 13, 2019
on Dryad.
https://doi.org/10.5061/dryad.kd1qt0p
Cite this dataset
Preska Steinberg, Asher et al. (2019). Data from: High-molecular-weight polymers from dietary fiber drive aggregation of particulates in the murine small intestine [Dataset]. Dryad. https://doi.org/10.5061/dryad.kd1qt0p
Abstract
The lumen of the small intestine (SI) is filled with particulates: microbes, therapeutic particles, and food granules. The structure of this particulate suspension could impact uptake of drugs and nutrients and the function of microorganisms; however, little is understood about how this suspension is re-structured as it transits the gut. Here, we demonstrate that particles spontaneously aggregate in SI luminal fluid ex vivo. We find that mucins and immunoglobulins are not required for aggregation. Instead, aggregation can be controlled using polymers from dietary fiber in a manner that is qualitatively consistent with polymer-induced depletion interactions, which do not require specific chemical interactions. Furthermore, we find that aggregation is tunable; by feeding mice dietary fibers of different molecular weights, we can control aggregation in SI luminal fluid. This work suggests that the molecular weight and concentration of dietary polymers play an underappreciated role in shaping the physicochemical environment of the gut.
Usage notes
Figure 2 - Source Data 1
This zip archive contains the original z-stack used for Figure 2, panels A-C. It is provided as a TIF file, which is readable by FIJI. All imaging parameters are included in the image metadata.
Figure 2 - Source Data 2
This zip archive contains the original z-stack used for Figure 2, panel D. It is provided as a TIF file, which is readable by FIJI. All imaging parameters are included in the image metadata.
Figure 2 - Source Data 3
This zip archive contains the original z-stack used for Figure 2, panel E. It is provided as a TIF file, which is readable by FIJI. All imaging parameters are included in the image metadata.
Figure 2 - Source Data 4
This zip archive contains the original z-stacks used for Figure 2, panels F-G. These are provided as TIF files, which are readable by FIJI. All imaging parameters are included in the image metadata. They are labeled by “Group#” (indicating which CDF they below to in the figure) and “Trial#” if multiple technical replicates were done for a given sample from a Group. The control done in Hanks’ Balanced Salt Solution (HBSS) is labeled as “HBSS”.
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “Group#_trial#_automated_counting_statistics”. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “Group#_trial#_singlet_IDs”. These .csv files were used in combination with the jupyter notebooks (also provided in this submission) to generate Figure 2, panels F-G. If multiple technical replicates were performed on a sample, the resulting ECDFs were combined to create one master ECDF for that sample.
Figure 2 - Source Data 5
This zip archive contains the original z-stacks used for Figure 2, panels H-I. These are provided as TIF files, which are readable by FIJI. All imaging parameters are included in the image metadata. They are labeled by “Group#” (indicating which CDF they below to in the figure) and “Trial#” if multiple technical replicates were done for a given sample from a Group. The control done in Hanks’ Balanced Salt Solution (HBSS) is labeled as “HBSS”.
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “Group#_trial#_automated_counting_statistics”. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “Group#_trial#_singlet_IDs”. These .csv files were used in combination with the jupyter notebooks provided (also provided in this submission) to generate Figure 2, panels H-I. If multiple technical replicates were performed on a sample, the resulting ECDFs were combined to create one master ECDF for that sample.
Figure 3 - Source Data 1
This zip archive contains the original z-stacks used for Figure 3, panels B-C. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows (if multiple technical replicates were done it is indicated): A7PS263_s1_t1 = 30 µm-filtered, technical replicate #1; A7PS263_s2_t1 = 0.45 µm-filtered; A7PS263_s3_t1 = 100 kDa-filtered; A7PS263_s4_t1 = 30 kDa-filtered; A7PS263_s5_t1 = 3 kDa-filtered; A7PS284_s13_t1 = HBSS; A7PS285_s1_t1 = 30 µm-filtered, technical replicate #2; A7PS285_s2_t1 = 0.45 µm-filtered, technical replicate #2; A7PS285_s5_t1 = 30 µm-filtered, technical replicate #3; A7PS285_s6_t1 = 0.45 µm-filtered, technical replicate #3.
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks (also provided with this submission) to generate Figure 3, panels B-C. If multiple technical replicates were performed on a sample, the resulting ECDFs were combined to create one master ECDF for that sample.
Figure 3 - Source Data 2
This zip archive contains the original z-stacks used for Figure 3, panels E-F. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows (if multiple technical replicates were done it is indicated): A7PS263_s6_t1 = 30 µm-filtered, technical replicate #1; A7PS263_s7_t1 = 0.45 µm-filtered; A7PS263_s8_t1 = 100 kDa-filtered; A7PS263_s9_t1 = 30 kDa-filtered; A7PS263_s10_t1 = 3 kDa-filtered; A7PS284_s13_t1 = HBSS; A7PS285_s3_t1 = 30 µm-filtered, technical replicate #2; A7PS285_s4_t1 = 0.45 µm-filtered, technical replicate #2; A7PS285_s7_t1 = 30 µm-filtered, technical replicate #3; A7PS285_s8_t1 = 0.45 µm-filtered, technical replicate #3.
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks (also provided with this submission) to generate Figure 3, panels E-F. If multiple technical replicates were performed on a sample, the resulting ECDFs were combined to create one master ECDF for that sample.
Figure 4 - source data 1
This zip archive contains the original z-stack used for Figure 4, panels A-C. It is provided as a TIF file. All imaging parameters are included in the image metadata.
Figure 4 - source data 2
This zip archive contains the original z-stacks used for the PEG 1 MDa data in Figure 4, panel D. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS290_s1_t1 = 6.52 mg/mL PEG 1 MDa
A7PS290_s2_t1 = 3.26 mg/mL PEG 1 MDa
A7PS290_s3_t1 = 1.63 mg/mL PEG 1 MDa
A7PS290_s4_t1 = 0.815 mg/mL PEG 1 MDa
A7PS290_s5_t1 = 0.407 mg/mL PEG 1 MDa
A7PS290_s6_t1 = 0.204 mg/mL PEG 1 MDa
A7PS290_s7_t1 = 0.102 mg/mL PEG 1 MDa
A7PS290_s8_t1 = 0.0509 mg/mL PEG 1 MDa
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks provided as additional files to this paper to generate Figure 4, panel D.
Figure 4 - source data 3
This zip archive contains the original z-stacks used for the PEG 100kDa data in Figure 4, panel D. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS290_s9_t1 = 34.4 mg/mL PEG 100 kDa
A7PS290_s10_t1 = 17.2 mg/mL PEG 100 kDa
A7PS290_s11_t1 = 8.59 mg/mL PEG 100 kDa
A7PS290_s12_t1 = 4.29 mg/mL PEG 100 kDa
A7PS290_s13_t1 = 2.15 mg/mL PEG 100 kDa
A7PS290_s14_t1 = 1.07 mg/mL PEG 100 kDa
A7PS290_s15_t1 = 0.536 mg/mL PEG 100 kDa
A7PS290_s16_t1 = 0.268 mg/mL PEG 100 kDa
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks provided as additional files to this paper to generate Figure 4, panel D.
Figure 4 - source data 4
This zip archive contains the original z-stacks used for Figure 4, panel D. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS290_s17_t1 = 212 mg/mL PEG 3.35 kDa
A7PS290_s18_t1 = 106 mg/mL PEG 3.35 kDa
A7PS290_s19_t1 = 53.0 mg/mL PEG 3.35 kDa
A7PS290_s20_t1 = 26.5 mg/mL PEG 3.35 kDa
A7PS290_s21_t1 = 13.2 mg/mL PEG 3.35 kDa
A7PS290_s22_t1 = 6.62 mg/mL PEG 3.35 kDa
A7PS290_s23_t1 = 3.31 mg/mL PEG 3.35 kDa
A7PS290_s24_t1 = 1.66 mg/mL PEG 3.35 kDa
A7PS321_s1_t1 = 0.815 mg/mL PEG 3.35 kDa
A7PS321_s2_t1 = 0.407 mg/mL PEG 3.35 kDa
A7PS321_s3_t1 = 0.204 mg/mL PEG 3.35 kDa
A7PS321_s4_t1 = 0.102 mg/mL PEG 3.35 kDa
A7PS321_s5_t1 = 0.0509 mg/mL PEG 3.35 kDa
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks (provided with this submission) to generate Figure 4, panel D.
Figure 5 - source data 1
This zip archive contains the original z-stacks used for Figure 5, panels A and C. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS303_s1_t1 = WT USI, Dilution factor = 1
A7PS303_s2_t1 = WT USI, Dilution factor = 1/2
A7PS303_s3_t1 = WT USI, Dilution factor = 1/4
A7PS303_s4_t1 = WT USI, Dilution factor = 1/8
A7PS303_s17_t1 = MUC2KO USI, Dilution factor = 1
A7PS303_s18_t1 = MUC2KO USI, Dilution factor = 1/2
A7PS303_s19_t1 = MUC2KO USI, Dilution factor = 1/4
A7PS303_s20_t1 = MUC2KO USI, Dilution factor = 1/8
A7PS284_s13_t1 = HBSS
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks (provided with this submission) to generate Figure 5, panels A and C.
Figure 5 - source data 2
This zip archive contains the original z-stacks used for Figure 5, panels B and D. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS303_s9_t1 = WT LSI, Dilution factor = 1
A7PS303_s10_t1 = WT LSI, Dilution factor = 1/2
A7PS303_s11_t1 = WT LSI, Dilution factor = 1/4
A7PS303_s12_t1 = WT LSI, Dilution factor = 1/8
A7PS303_s25_t1 = MUC2KO LSI, Dilution factor = 1
A7PS303_s26_t1 = MUC2KO LSI, Dilution factor = 1/2
A7PS303_s27_t1 = MUC2KO LSI, Dilution factor = 1/4
A7PS303_s28_t1 = MUC2KO LSI, Dilution factor = 1/8
A7PS284_s13_t1 = HBSS
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks (provided with this submission) to generate Figure 5, panels B and D.
Figure 6 - source data 1
This zip archive contains the original z-stacks used for Figure 6, panels A and C. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS309_s1_t1 = WT USI, Dilution factor = 1
A7PS309_s2_t1 = WT USI, Dilution factor = 1/2
A7PS309_s3_t1 = WT USI, Dilution factor = 1/4
A7PS309_s4_t1 = WT USI, Dilution factor = 1/8
A7PS309_s17_t1 = Rag1KO USI, Dilution factor = 1
A7PS309_s18_t1 = Rag1KO USI, Dilution factor = 1/2
A7PS309_s19_t1 = Rag1KO USI, Dilution factor = 1/4
A7PS309_s20_t1 = Rag1KO USI, Dilution factor = 1/8
A7PS284_s13_t1 = HBSS
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks (provided with this submission) to generate Figure 6, panels A and C.
Figure 6 - source data 2
This zip archive contains the original z-stacks used for Figure 6, panels B and D. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS309_s9_t1 = WT LSI, Dilution factor = 1
A7PS309_s10_t1 = WT LSI, Dilution factor = 1/2
A7PS309_s11_t1 = WT LSI, Dilution factor = 1/4
A7PS309_s12_t1 = WT LSI, Dilution factor = 1/8
A7PS309_s25_t1 = Rag1KO LSI, Dilution factor = 1
A7PS309_s26_t1 = Rag1KO LSI, Dilution factor = 1/2
A7PS309_s27_t1 = Rag1KO LSI, Dilution factor = 1/4
A7PS309_s28_t1 = Rag1KO LSI, Dilution factor = 1/8
A7PS284_s13_t1 = HBSS
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks (provided with this submission) to generate Figure 6, panels B and D.
Figure 7 - source data 1
This zip archive contains the original z-stacks used for Figure 7, panel A. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS320_s1_t1 = 6.66 mg/mL Pectin
A7PS320_s2_t1 = 3.33 mg/mL Pectin
A7PS320_s3_t1 = 1.67 mg/mL Pectin
A7PS320_s4_t1 = 0.835 mg/mL Pectin
A7PS320_s5_t1 = 0.417 mg/mL Pectin
A7PS320_s6_t1 = 0.209 mg/mL Pectin
A7PS320_s7_t1 = 0.105 mg/mL Pectin
A7PS320_s8_t1 = 0.053 mg/mL Pectin
A7PS320_s11_t1 = 236 mg/mL Fibersol-2
A7PS320_s12_t1 = 118 mg/mL Fibersol-2
A7PS320_s13_t1 = 59.0 mg/mL Fibersol-2
A7PS320_s14_t1 = 29.5 mg/mL Fibersol-2
A7PS320_s15_t1 = 14.8 mg/mL Fibersol-2
A7PS322_s1_t1 = 6.66 mg/mL Fibersol-2
A7PS322_s2_t1 = 3.33 mg/mL Fibersol-2
A7PS322_s3_t1 = 1.67 mg/mL Fibersol-2
A7PS322_s4_t1 = 0.835 mg/mL Fibersol-2
A7PS322_s5_t1 = 0.417 mg/mL Fibersol-2
A7PS322_s6_t1 = 0.209 mg/mL Fibersol-2
A7PS322_s7_t1 = 0.105 mg/mL Fibersol-2
A7PS322_s8_t1 = 0.053 mg/mL Fibersol-2
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks (provided with this submission) to this paper to generate Figure 7, panel A.
Figure 7 - source data 2
This zip archive contains the original z-stacks used for Figure 7, panel E. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS313_s17_t1 = 30-µm-filtered Pectin USI, Dilution factor = 1
A7PS313_s18_t1 = 30-µm-filtered Pectin USI, Dilution factor = 1/2
A7PS313_s19_t1 = 30-µm-filtered Pectin USI, Dilution factor = 1/4
A7PS313_s20_t1 = 30-µm-filtered Pectin USI, Dilution factor = 1/8
A7PS313_s21_t1 = 30-µm-filtered Pectin USI, Dilution factor = 1/16
A7PS313_s22_t1 = 30-µm-filtered Pectin USI, Dilution factor = 1/32
A7PS313_s23_t1 = 30-µm-filtered Pectin USI, Dilution factor = 1/64
A7PS313_s24_t1 = 30-µm-filtered Pectin USI, Dilution factor = 1/128
A7PS314_s17_t1 = 30-µm-filtered Fibersol-2 USI, Dilution factor = 1
A7PS314_s18_t1 = 30-µm-filtered Fibersol-2 USI, Dilution factor = 1/2
A7PS314_s19_t1 = 30-µm-filtered Fibersol-2 USI, Dilution factor = 1/4
A7PS314_s20_t1 = 30-µm-filtered Fibersol-2 USI, Dilution factor = 1/8
A7PS314_s21_t1 = 30-µm-filtered Fibersol-2 USI, Dilution factor = 1/16
A7PS314_s22_t1 = 30-µm-filtered Fibersol-2 USI, Dilution factor = 1/32
A7PS314_s23_t1 = 30-µm-filtered Fibersol-2 USI, Dilution factor = 1/64
A7PS314_s24_t1 = 30-µm-filtered Fibersol-2 USI, Dilution factor = 1/128
A7PS284_s13_t1 = HBSS
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks (provided with this submission) to generate Figure 7, panel E.
Figure 7 - source data 3
This zip archive contains the original z-stacks used for Figure 7, panel F. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS313_s1_t1 = 0.45-µm-filtered Pectin USI, Dilution factor = 1
A7PS313_s2_t1 = 0.45-µm-filtered Pectin USI, Dilution factor = 1/2
A7PS313_s3_t1 = 0.45-µm-filtered Pectin USI, Dilution factor = 1/4
A7PS313_s4_t1 = 0.45-µm-filtered Pectin USI, Dilution factor = 1/8
A7PS313_s5_t1 = 0.45-µm-filtered Pectin USI, Dilution factor = 1/16
A7PS313_s6_t1 = 0.45-µm-filtered Pectin USI, Dilution factor = 1/32
A7PS313_s7_t1 = 0.45-µm-filtered Pectin USI, Dilution factor = 1/64
A7PS313_s8_t1 = 0.45-µm-filtered Pectin USI, Dilution factor = 1/128
A7PS314_s1_t1 = 0.45-µm-filtered Fibersol-2 USI, Dilution factor = 1
A7PS314_s2_t1 = 0.45-µm-filtered Fibersol-2 USI, Dilution factor = 1/2
A7PS314_s3_t1 = 0.45-µm-filtered Fibersol-2 USI, Dilution factor = 1/4
A7PS314_s4_t1 = 0.45-µm-filtered Fibersol-2 USI, Dilution factor = 1/8
A7PS314_s5_t1 = 0.45-µm-filtered Fibersol-2 USI, Dilution factor = 1/16
A7PS314_s6_t1 = 0.45-µm-filtered Fibersol-2 USI, Dilution factor = 1/32
A7PS314_s7_t1 = 0.45-µm-filtered Fibersol-2 USI, Dilution factor = 1/64
A7PS314_s8_t1 = 0.45-µm-filtered Fibersol-2 USI, Dilution factor = 1/128
A7PS284_s13_t1 = HBSS
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks (provided with this submission) to generate Figure 7, panel F.
Figure 7 - source data 4
This zip archive contains the original z-stacks used for Figure 7, panel G. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS318_s1_t1 = 30-µm-filtered Pectin LSI, Dilution factor = 1/4
A7PS318_s2_t1 = 30-µm-filtered Pectin LSI, Dilution factor = 1/8
A7PS318_s3_t1 = 30-µm-filtered Pectin LSI, Dilution factor = 1/16
A7PS318_s4_t1 = 30-µm-filtered Pectin LSI, Dilution factor = 1/32
A7PS318_s5_t1 = 30-µm-filtered Pectin LSI, Dilution factor = 1/64
A7PS318_s6_t1 = 30-µm-filtered Pectin LSI, Dilution factor = 1/128
A7PS314_s25_t1 = 30-µm-filtered Fibersol-2 LSI, Dilution factor = 1
A7PS314_s26_t1 = 30-µm-filtered Fibersol-2 LSI, Dilution factor = 1/2
A7PS314_s27_t1 = 30-µm-filtered Fibersol-2 LSI, Dilution factor = 1/4
A7PS314_s28_t1 = 30-µm-filtered Fibersol-2 LSI, Dilution factor = 1/8
A7PS314_s29_t1 = 30-µm-filtered Fibersol-2 LSI, Dilution factor = 1/16
A7PS314_s30_t1 = 30-µm-filtered Fibersol-2 LSI, Dilution factor = 1/32
A7PS314_s31_t1 = 30-µm-filtered Fibersol-2 LSI, Dilution factor = 1/64
A7PS314_s32_t1 = 30-µm-filtered Fibersol-2 LSI, Dilution factor = 1/128
A7PS284_s13_t1 = HBSS
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks (provided with this submission) to generate Figure 7, panel G.
Figure 7 - source data 5
This zip archive contains the original z-stacks used for Figure 7, panel H. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS313_s9_t1 = 0.45-µm-filtered Pectin LSI, Dilution factor = 1
A7PS313_s10_t1 = 0.45-µm-filtered Pectin LSI, Dilution factor = 1/2
A7PS313_s11_t1 = 0.45-µm-filtered Pectin LSI, Dilution factor = 1/4
A7PS313_s12_t1 = 0.45-µm-filtered Pectin LSI, Dilution factor = 1/8
A7PS313_s13_t1 = 0.45-µm-filtered Pectin LSI, Dilution factor = 1/16
A7PS313_s14_t1 = 0.45-µm-filtered Pectin LSI, Dilution factor = 1/32
A7PS313_s15_t1 = 0.45-µm-filtered Pectin LSI, Dilution factor = 1/64
A7PS313_s16_t1 = 0.45-µm-filtered Pectin LSI, Dilution factor = 1/128
A7PS314_s9_t1 = 0.45-µm-filtered Fibersol-2 LSI, Dilution factor = 1
A7PS314_s10_t1 = 0.45-µm-filtered Fibersol-2 LSI, Dilution factor = 1/2
A7PS314_s11_t1 = 0.45-µm-filtered Fibersol-2 LSI, Dilution factor = 1/4
A7PS314_s12_t1 = 0.45-µm-filtered Fibersol-2 LSI, Dilution factor = 1/8
A7PS314_s13_t1 = 0.45-µm-filtered Fibersol-2 LSI, Dilution factor = 1/16
A7PS314_s14_t1 = 0.45-µm-filtered Fibersol-2 LSI, Dilution factor = 1/32
A7PS314_s15_t1 = 0.45-µm-filtered Fibersol-2 LSI, Dilution factor = 1/64
A7PS314_s16_t1 = 0.45-µm-filtered Fibersol-2 LSI, Dilution factor = 1/128
A7PS284_s13_t1 = HBSS
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks (provided with this submission) to generate Figure 7, panel H.
Figure 5 - figure supplement 1 - source data 1
This zip archive contains the original z-stacks used for This zip archive contains the original z-stacks used for Figure 5 - figure supplement 1, panels A and C. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS302_s1_t1 = WT USI, Dilution factor = 1
A7PS302_s2_t1 = WT USI, Dilution factor = 1/2
A7PS302_s3_t1 = WT USI, Dilution factor = 1/4
A7PS302_s4_t1 = WT USI, Dilution factor = 1/8
A7PS302_s17_t1 = MUC2KO USI, Dilution factor = 1
A7PS302_s18_t1 = MUC2KO USI, Dilution factor = 1/2
A7PS302_s19_t1 = MUC2KO USI, Dilution factor = 1/4
A7PS302_s20_t1 = MUC2KO USI, Dilution factor = 1/8
A7PS284_s13_t1 = HBSS
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks (provided with this submission) to generate Figure 5 - figure supplement 1, panels A and C.
Figure 5 - figure supplement 1 - source data 2
This zip archive contains the original z-stacks used for Figure 5 - figure supplement 1, panels B and D. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS302_s9_t1 = WT LSI, Dilution factor = 1
A7PS302_s10_t1 = WT LSI, Dilution factor = 1/2
A7PS302_s11_t1 = WT LSI, Dilution factor = 1/4
A7PS302_s12_t1 = WT LSI, Dilution factor = 1/8
A7PS302_s25_t1 = MUC2KO LSI, Dilution factor = 1
A7PS302_s26_t1 = MUC2KO LSI, Dilution factor = 1/2
A7PS302_s27_t1 = MUC2KO LSI, Dilution factor = 1/4
A7PS302_s28_t1 = MUC2KO LSI, Dilution factor = 1/8
A7PS284_s13_t1 = HBSS
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks (provided with this submission) to generate Figure 5 - figure supplement 1, panels B and D.
Figure 6 - figure supplement 3 - source data 1
This zip archive contains the original z-stacks used for Figure 6 - figure supplement 3, panels A and C. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS308_s1_t1 = WT USI, Dilution factor = 1
A7PS308_s2_t1 = WT USI, Dilution factor = 1/2
A7PS308_s3_t1 = WT USI, Dilution factor = 1/4
A7PS308_s4_t1 = WT USI, Dilution factor = 1/8
A7PS308_s17_t1 = Rag1KO USI, Dilution factor = 1
A7PS308_s18_t1 = Rag1KO USI, Dilution factor = 1/2
A7PS308_s19_t1 = Rag1KO USI, Dilution factor = 1/4
A7PS308_s20_t1 = Rag1KO USI, Dilution factor = 1/8
A7PS284_s13_t1 = HBSS
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks (provided with this submission) to generate Figure 6 - figure supplement 3, panels A and C.
Figure 6 - figure supplement 3 - source data 2
This zip archive contains the original z-stacks used for Figure 6 - figure supplement 3, panels B and D. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS308_s9_t1 = WT LSI, Dilution factor = 1
A7PS308_s10_t1 = WT LSI, Dilution factor = 1/2
A7PS308_s11_t1 = WT LSI, Dilution factor = 1/4
A7PS308_s12_t1 = WT LSI, Dilution factor = 1/8
A7PS308_s25_t1 = Rag1KO LSI, Dilution factor = 1
A7PS308_s26_t1 = Rag1KO LSI, Dilution factor = 1/2
A7PS308_s27_t1 = Rag1KO LSI, Dilution factor = 1/4
A7PS308_s28_t1 = Rag1KO LSI, Dilution factor = 1/8
A7PS284_s13_t1 = HBSS
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks (provided with this submission) to generate Figure 6 - figure supplement 3, panels B and D.
Table 2 - source data 1
This zip archive contains the chromatography data that was used to calculate the values displayed in Table 2. “WT_USI_raw_data.xlsx” contains the data for the wild-type upper small intestine, “KO_USI_raw_data.xlsx” contains the data for the MUC2 knockout upper small intestine. In both the excel files, RI = refractive index, RALS = Right-angle light scattering, LALS = low-angle light scattering, DP = differential pressure (the viscometer). All values are measured in millivolts except for retention volume, which is measured in milliliters (mL).
The file “Table S1 – source data 1.OmnisecArchive” contains all this data, along with the data for the pullulan and dextran standard that were used to calibrate the instrument. This can be used in conjunction with Malvern OMNISEC v10.20 software to reproduce the calculations displayed in the table.
Table 3 - source data 1
This zip archive contains the chromatography data that was used to calculate the values displayed in Table 3. “WT_LSI_raw_data.xlsx” contains the data for the wild-type lower small intestine, “KO_LSI_raw_data.xlsx” contains the data for the MUC2 knockout lower small intestine. In both the excel files, RI = refractive index, RALS = Right-angle light scattering, LALS = low-angle light scattering, DP = differential pressure (the viscometer). All values are measured in millivolts except for retention volume, which is measured in milliliters (mL).
The file “Table S2 – source data 1.OmnisecArchive” contains all this data, along with the data for the pullulan and dextran standard that were used to calibrate the instrument. This can be used in conjunction with Malvern OMNISEC v10.20 software to reproduce the calculations displayed in the table.
Table 4 - source data 1
This zip archive contains the chromatography data that was used to calculate the values displayed in Table 4. “WT_USI_raw_data.xlsx” contains the data for the wild-type upper small intestine, “Rag1KO_USI_raw_data.xlsx” contains the data for the immunoglobulin-deficient (Rag1KO) upper small intestine. In both the excel files, RI = refractive index, RALS = Right-angle light scattering, LALS = low-angle light scattering, DP = differential pressure (the viscometer). All values are measured in millivolts except for retention volume, which is measured in milliliters (mL).
The file “Table S3 – source data 1.OmnisecArchive” contains all this data, along with the data for the pullulan and dextran standard that were used to calibrate the instrument. This can be used in conjunction with Malvern OMNISEC v10.20 software to reproduce the calculations displayed in the table. LALS data was not used for these calculations because of the noisiness of the signal from the detector.
Table 5 - source data 1
This zip archive contains the chromatography data that was used to calculate the values displayed in Table 5. “WT_LSI_raw_data.xlsx” contains the data for the wild-type lower small intestine, “Rag1KO_LSI_raw_data.xlsx” contains the data for the immunoglobulin-deficient (Rag1KO) lower small intestine. In both the excel files, RI = refractive index, RALS = Right-angle light scattering, LALS = low-angle light scattering, DP = differential pressure (the viscometer). All values are measured in millivolts except for retention volume, which is measured in milliliters (mL).
The file “Table S4 – source data 1.OmnisecArchive” contains all this data, along with the data for the pullulan and dextran standard that were used to calibrate the instrument. This can be used in conjunction with Malvern OMNISEC v10.20 software to reproduce the calculations displayed in the table. LALS data was not used for these calculations because of the noisiness of the signal from the detector.
Table 6 - source data 1
This zip archive contains the chromatography data that was used to calculate the values displayed in Table 6. “pectin_raw_data.xlsx” contains the data for pectin, “fibersol-2_raw_data.xlsx” contains the data for Fibersol-2. In both the excel files, RI = refractive index, RALS = Right-angle light scattering, LALS = low-angle light scattering, DP = differential pressure (the viscometer). All values are measured in millivolts except for retention volume, which is measured in milliliters (mL).
The file “Table S5 – pectin source data” contains all the data for pectin, along with the data for the pullulan and dextran standard that were used to calibrate the instrument for this run. The file “Table S5 – fibersol-2 source data” contains all the data for Fibersol-2, along with the data for the pullulan and dextran standard that were used to calibrate the instrument for this run. This can be used in conjunction with Malvern OMNISEC v10.20 software to reproduce the calculations displayed in the table. LALS data was not used for these calculations because of the noisiness of the signal from the detector.
Table 7 - source data 1
This zip archive contains the chromatography data that was used to calculate the values displayed in Table 7. “pectin_USI_raw_data.xlsx” contains the data for the upper small intestine of pectin-fed mice, “Fibersol-2_USI_raw_data.xlsx” contains the data for the upper small intestine of Fibersol-2-fed mice. In both the excel files, RI = refractive index, RALS = Right-angle light scattering, LALS = low-angle light scattering, DP = differential pressure (the viscometer). All values are measured in millivolts except for retention volume, which is measured in milliliters (mL).
The file “Table S6 – source data 1” contains all the data, along with the data for the pullulan and dextran standard that were used to calibrate the instrument. This can be used in conjunction with Malvern OMNISEC v10.20 software to reproduce the calculations displayed in the table. LALS data was not used for these calculations because of the noisiness of the signal from the detector.
Table 8 - source data 1
This zip archive contains the chromatography data that was used to calculate the values displayed in Table 8. “pectin_LSI_raw_data.xlsx” contains the data for the lower small intestine of pectin-fed mice, “Fibersol-2_LSI_raw_data.xlsx” contains the data for the lower small intestine of Fibersol-2-fed mice. In both the excel files, RI = refractive index, RALS = Right-angle light scattering, LALS = low-angle light scattering, DP = differential pressure (the viscometer). All values are measured in millivolts except for retention volume, which is measured in milliliters (mL).
The file “Table S7 – source data 1” contains all the data, along with the data for the pullulan and dextran standard that were used to calibrate the instrument. This can be used in conjunction with Malvern OMNISEC v10.20 software to reproduce the calculations displayed in the table. LALS data was not used for these calculations because of the noisiness of the signal from the detector.
Aggregate Image Analysis Code
These FIJI ImageJ macros were used to determine volumes of aggregates of particles in z-stacks.
"Aggregate_Counting_Macro_1.2.4_for_publication.ijm" takes in a z-stack and generates various statistics about aggregates including volume, surface area, and position. Results for Test_dataset_08_01_18 are located in the Results folder.
"Average_Singlet_Size_Macro_1.0.0_for_publication.ijm" takes the object map output from the Aggregate_Counting_Macro and prompts the user to record the ID number associated with 10 single particles. The singlets can then be used to convert aggregate volumes from the Aggregate_Counting_Macro into particle counts.
Written in the ImageJ macro language.
Test dataset was run in FIJI version 2.00-rc-68/1.52e, Build:bad6864e55 using macOS Version 10.13.4.
Bootstrap confidence intervals code
This zip folder contains the source code to generate 95% empirical bootstrap confidence intervals. The .html and .ipynb files are identical. The code was written with Python version 3.6.4. It has been verified to work with numpy version 1.13.3, pandas version 0.21.1, scipy version 1.0.0, bokeh version 0.12.15, holoviews version 1.9.1, and numba version 0.36.2.
The test data folder provides data that can be used to verify that the code is working. Make sure to change the file paths to what is appropriate for your computer. The test data will reproduce Figure 7G from the main text. This data was also provided as part of “Figure 7 – source data 4”.
volume-weighted ECDF code
This zip folder contains the source code to generate 95% empirical bootstrap confidence intervals The .html and .ipynb file are identical. The code was written with Python version 3.6.4. It has been verified to work with numpy version 1.13.3, pandas version 0.21.1, scipy version 1.0.0, bokeh version 0.12.15, and holoviews version 1.9.1.
The test data folder provides data that can be used to verify that the code is working. Make sure to change the file paths to what is appropriate for your computer. The test data will reproduce Figure 5, Panel A from the main text. This data was also provided as part of “Figure 5 – source data 1”.
Depletion Calculations Code
This zip folder contains the source code to generate the plots of the interparticle potential minima displayed in Figure 4H. The .html and .ipynb file are identical. The code was written with Python version 3.6.4. It has been verified to work with numpy version 1.13.3, pandas version 0.21.1, scipy version 1.0.0, bokeh version 0.12.15, sympy version 1.1.1, holoviews version 1.9.1, and numba version 0.36.2.
Diffusion coefficients Code
This zip folder contains the source code to generate the plots of the diffusion coefficients displayed in Figure 4I. The .html and .ipynb file are identical. The code was written with Python version 3.6.4. It has been verified to work with numpy version 1.13.3, pandas version 0.21.1, scipy version 1.0.0, bokeh version 0.12.15, sympy version 1.1.1, holoviews version 1.9.1, and numba version 0.36.2.
Figure 4 - figure supplement 2
This zip archive contains the original z-stacks used for the PEG 1 MDa data in Figure 4, figure supplement 2.. These are provided as TIF files. All imaging parameters are included in the image metadata. They are labeled as follows:
A7PS362_s1_t1 = 6.52 mg/mL PEG 1 MDa
A7PS362_s2_t1 = 3.26 mg/mL PEG 1 MDa
A7PS362_s3_t1 = 1.63 mg/mL PEG 1 MDa
A7PS362_s4_t1 = 0.815 mg/mL PEG 1 MDa
A7PS362_s5_t1 = 0.407 mg/mL PEG 1 MDa
A7PS362_s6_t1 = 0.204 mg/mL PEG 1 MDa
A7PS362_s7_t1 = 0.102 mg/mL PEG 1 MDa
A7PS362_s8_t1 = 0.0509 mg/mL PEG 1 MDa
Additionally, this file contains .csv files of all the statistics on particle sizes collected by the ImageJ macro. These are labeled in the format “zstackname_automated_counting_statistics”, where “zstackname” is the title of the associated z-stack. It also contains a .csv file of the particle # IDs of the singlet particles that were used to get the average singlet size, which was then used to normalize the ECDFs (as explained in detail in Materials and Methods). These are labeled in the format “zstackname_singlet_IDs”, where “zstackname” is the title of the associated z-stack. These .csv files were used in combination with the Jupyter notebooks provided as additional files to this paper to generate Figure 4, figure supplement 2.
Funding
National Science Foundation, Award: DGE-144469