DOI: 10.5061/dryad.kd1qt0p
title: Data from: High-molecular-weight polymers from dietary fiber drive aggregation of particulates in the murine small intestine

description: 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.
description: Figure 2 - Source Data
 1This
 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
 2This
 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
 3This
 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
 4This
 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
 5This
 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
 1This
 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
 2This
 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
 1This
 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
 2This
 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
 3This
 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
 4This
 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
 1This
 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
 2This
 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
 1This
 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
 2This
 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
 1This
 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
 2This
 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
 3This
 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
 4This
 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
 5This
 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 1This 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 2This 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 1This 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 2This 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
 1This
 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
 1This
 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
 1This
 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
 1This
 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
 1This
 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
 1This
 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
 1This
 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
 CodeThese 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 codeThis 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
 codeThis 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
 CodeThis 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
 CodeThis 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 2This 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.