From 4f51eca77cb6bc7d9935838e37728776ea197afe Mon Sep 17 00:00:00 2001 From: ndwarshuis Date: Wed, 4 Aug 2021 14:13:06 -0400 Subject: [PATCH] ENH almost proofread aim 1 --- tables/luminex_panel.tex | 1 - tex/references.bib | 13 + tex/thesis.tex | 589 ++++++++++++++++++++------------------- 3 files changed, 308 insertions(+), 295 deletions(-) diff --git a/tables/luminex_panel.tex b/tables/luminex_panel.tex index f7f6671..e23182c 100644 --- a/tables/luminex_panel.tex +++ b/tables/luminex_panel.tex @@ -33,6 +33,5 @@ MIP-1$\upalpha$ & 10 & 2\\ MIP-1$\upbeta$ & 10 & 2\\ RANTES & 10 & 2\\ - TGF$\upbeta$ & 1 & 3\\ \hline \end{tabular} \ No newline at end of file diff --git a/tex/references.bib b/tex/references.bib index a0e76da..1f9fb3c 100644 --- a/tex/references.bib +++ b/tex/references.bib @@ -2660,6 +2660,19 @@ CONCLUSIONS: We developed a simplified, semi-closed system for the initial selec publisher = {Massachusetts Medical Society}, } +@Article{Waysbort2013, + author = {Nir Waysbort and Dor Russ and Benjamin M. Chain and Nir Friedman}, + journal = {The Journal of Immunology}, + title = {Coupled {IL}-2{\textendash}Dependent Extracellular Feedbacks Govern Two Distinct Consecutive Phases of {CD}4 T Cell Activation}, + year = {2013}, + month = {nov}, + number = {12}, + pages = {5822--5830}, + volume = {191}, + doi = {10.4049/jimmunol.1301575}, + publisher = {The American Association of Immunologists}, +} + @Comment{jabref-meta: databaseType:bibtex;} @Comment{jabref-meta: grouping: diff --git a/tex/thesis.tex b/tex/thesis.tex index 0c41ace..3e6a3a7 100644 --- a/tex/thesis.tex +++ b/tex/thesis.tex @@ -199,12 +199,14 @@ \newacronym{zfn}{ZFN}{zinc-finger nuclease} \newacronym{talen}{TALEN}{transcription activator-like effector nuclease} \newacronym{qbd}{QbD}{quality-by-design} -\newacronym{aws}{AWS}{amazon web services} +\newacronym{aws}{AWS}{Amazon Web Services} \newacronym{qpcr}{qPCR}{quantitative polymerase chain reaction} \newacronym{cstr}{CSTR}{continuously stirred tank bioreactor} \newacronym{esc}{ESC}{embryonic stem cell} \newacronym{msc}{MSC}{mesenchymal stromal cells} \newacronym{scfv}{scFv}{single-chain fragment variable} +\newacronym{hepes}{HEPES}{4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid} +\newacronym{nhs}{NHS}{N-hydroxysulfosuccinimide} %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % SI units for uber nerds @@ -289,6 +291,7 @@ \newcommand{\catnum}[2]{(#1, #2)} \newcommand{\product}[3]{#1 \catnum{#2}{#3}} \newcommand{\thermo}{Thermo Fisher} +\newcommand{\gehc}{GE Healthcare} \newcommand{\sigald}{Sigma Aldrich} \newcommand{\miltenyi}{Miltenyi Biotech} \newcommand{\bl}{Biolegend} @@ -1266,23 +1269,9 @@ microcarriers functionalized with \acd{3} and \acd{28} \glspl{mab} will provide superior expansion and memory phenotype compared to state-of-the-art bead-based T cell expansion technology. -% TODO this doesn't flow that well and is repetitive with what comes above - -Microcarriers have been used throughout the bioprocess industry for adherent -cell cultures such as \gls{cho} cells and stem cells, as they are able to -achieve much greater surface area per unit volume than traditional 2D -cultures\cite{Heathman2015, Sart2011}. Adding adhesive \glspl{mab} to the -microcarriers will adapt them for suspension cell cultures such as T cells. -Consequently, the large macroporous structure will allow T cells to cluster more -closely, which in turn will enable better autocrine and paracrine signaling. -Specifically, two cytokines that are secreted by T cells, IL-2 and IL-15, are -known to drive expansion and memory phenotype respectively\cite{Buck2016}. -Therefore, the proposed microcarrier system should enable greater expansion and -better retention of memory phenotype compared to current bead-based methods. - \section{methods} -\subsection{dms functionalization}\label{sec:dms_fab} +\subsection{DMS functionalization}\label{sec:dms_fab} \begin{figure*}[ht!] \begingroup @@ -1294,24 +1283,23 @@ better retention of memory phenotype compared to current bead-based methods. \label{fig:dms_flowchart} \end{figure*} -Gelatin microcarriers (\gls{cus} or \gls{cug}, GE Healthcare, DG-2001-OO and -DG-0001-OO) were suspended at \SI{20}{\mg\per\ml} in 1X \gls{pbs} and -autoclaved. All subsequent steps were done aseptically, and all reactions were -carried out at \SI{20}{\mg\per\ml} carriers at room temperature and agitated -using an orbital shaker with a \SI{3}{\mm} orbit diameter. After autoclaving, -the microcarriers were washed using sterile \gls{pbs} three times in a 10:1 -volume ratio. \product{\Gls{snb}}{\thermo}{21217} was dissolved at -approximately \SI{10}{\uM} in sterile ultrapure water, and the true -concentration was then determined using the \gls{haba} assay (see below). -\SI{5}{\ul\of{\ab}\per\mL} \gls{pbs} was added to carrier suspension and allowed -to react for \SI{60}{\minute} at \SI{700}{\rpm} of agitation. After the -reaction, the amount of biotin remaining in solution was quantified using the -\gls{haba} assay (see below). The carriers were then washed three times, which -entailed adding sterile \gls{pbs} in a 10:1 volumetric ratio, agitating at -\SI{900}{\rpm} for \SI{10}{\minute}, adding up to a 15:1 volumetric ratio -(relative to reaction volume) of sterile \gls{pbs}, centrifuging at -\SI{1000}{\gforce} for \SI{1}{\minute}, and removing all liquid back down to the -reaction volume. +\product{\gls{cus}}{\gehc}{DG-2001-OO} or \product{\gls{cug}}{\gehc}{DG-0001-OO} +were suspended at \SI{20}{\mg\per\ml} in 1X \gls{pbs} and autoclaved. All +subsequent steps were done aseptically, and all reactions were carried out at +\SI{20}{\mg\per\ml} carriers at room temperature and agitated using an orbital +shaker with a \SI{3}{\mm} orbit diameter. After autoclaving, the microcarriers +were washed using sterile \gls{pbs} three times in a 10:1 volume ratio. +\product{\Gls{snb}}{\thermo}{21217} was dissolved at approximately \SI{10}{\uM} +in sterile ultrapure water, and the true concentration was then determined using +the \gls{haba} assay (see below). \SI{5}{\ul\of{\ab}\per\mL} \gls{pbs} was added +to carrier suspension and allowed to react for \SI{60}{\minute} at +\SI{700}{\rpm} of agitation. After the reaction, the amount of biotin remaining +in solution was quantified using the \gls{haba} assay (see below). The carriers +were then washed three times, which entailed adding sterile \gls{pbs} in a 10:1 +volumetric ratio, agitating at \SI{900}{\rpm} for \SI{10}{\minute}, adding up to +a 15:1 volumetric ratio (relative to reaction volume) of sterile \gls{pbs}, +centrifuging at \SI{1000}{\gforce} for \SI{1}{\minute}, and removing all liquid +back down to the reaction volume. To coat with \gls{stp}, \SI{40}{\ug\per\mL} \product{\gls{stp}}{Jackson Immunoresearch}{016-000-114} was added and allowed to react for @@ -1332,13 +1320,19 @@ sampled to quantify remaining \gls{mab} concentration using an step to remove excess \gls{stp}. They were washed once again in the cell culture media to be used for the T cell expansion. +\begin{table}[!h] \centering + \caption{Properties of the microcarriers used} + \label{tab:carrier_props} + \input{../tables/carrier_properties.tex} +\end{table} + The concentration of the final \gls{dms} suspension was found by taking a \SI{50}{\uL} sample, plating in a well, and imaging the entire well. The image was then manually counted to obtain a concentration. Surface area for \si{\ab\per\um\squared} was calculated using the properties for \gls{cus} and -\gls{cug} as given by the manufacturer {Table X}. +\gls{cug} as given by the manufacturer \cref{tab:carrier_props}. -\subsection{dms quality control assays} +\subsection{DMS quality control assays} Biotin was quantified using the \product{\gls{haba} assay}{\sigald}{H2153-1VL}. In the case of quantifying \gls{snb} prior to adding it to the microcarriers, @@ -1350,15 +1344,15 @@ Spectrophotometer using \product{\SI{70}{\ul} cuvettes}{BrandTech}{759200}. The extinction coefficient at \SI{500}{\nm} for \gls{haba}/avidin was assumed to be \SI{34000}{\per\cm\per\molar}. -\gls{stp} binding to the carriers was quantified indirectly using a +The \gls{stp} binding to the microcarriers was quantified indirectly using a \product{\gls{bca} kit}{\thermo}{23227} according to the manufacturer’s instructions, with the exception that the standard curve was made with known concentrations of purified \gls{stp} instead of \gls{bsa}. Absorbance at -\SI{592}{\nm} was quantified using a Biotek plate reader. +\SI{592}{\nm} was quantified using a BioTek plate reader. -\Gls{mab} binding to the microcarriers was quantified indirectly using an +The \gls{mab} binding to the microcarriers was quantified indirectly using an \gls{elisa} assay per the manufacturer’s instructions, with the exception that -the same antibodies used to coat the carriers were used as the standard for the +the same \glspl{mab} used to coat the carriers were used as the standard for the \gls{elisa} standard curve. Open biotin binding sites on the \glspl{dms} after \gls{stp} coating was @@ -1366,18 +1360,18 @@ quantified indirectly using \product{\gls{fitcbt}}{\thermo}{B10570}. Briefly, \SI{400}{\pmol\per\ml} \gls{fitcbt} were added to \gls{stp}-coated carriers and allowed to react for \SI{20}{\minute} at room temperature under constant agitation. The supernatant was quantified against a standard curve of -\gls{fitcbt} using a Biotek plate reader. +\gls{fitcbt} using a BioTek plate reader. \Gls{stp} binding was verified after the \gls{stp}-binding step visually by adding \gls{fitcbt} to the \gls{stp}-coated \glspl{dms}, resuspending in \SI{1}{\percent} agarose gel, and imaging on a \product{lightsheet - microscope}{Zeiss}{Z.1}. \Gls{mab} binding was verified visually by first -staining with \product{\anti{\gls{igg}}-\gls{fitc}}{\bl}{406001}, incubating for -\SI{30}{\minute}, washing with \gls{pbs}, and imaging on a confocal microscope. + microscope}{Zeiss}{Z.1}. Overall \gls{mab} binding was verified visually +by first staining with \product{\anti{\gls{igg}}-\gls{fitc}}{\bl}{406001}, +incubating for \SI{30}{\minute}, washing with \gls{pbs}, and imaging on a +confocal microscope. \subsection{t cell culture}\label{sec:tcellculture} -% TODO verify countess product number Cryopreserved primary human T cells were either obtained as sorted \product{\cdp{3} T cells}{Astarte Biotech}{1017} or isolated from \product{\glspl{pbmc}}{Zenbio}{SER-PBMC} using a negative selection @@ -1390,15 +1384,15 @@ otherwise noted. Initial cell density was \SIrange{2e6}{2.5e6}{\cell\per\ml} to in a 96 well plate with \SI{300}{\ul} volume. Serum-free media was either \product{OpTmizer}{\thermo}{A1048501} or \product{TexMACS}{\miltenyi}{170-076-307} supplemented with -\SIrange{100}{400}{\IU\per\ml} \product{\gls{rhil2}}{Peprotech}{200-02}. Cell -cultures were expanded for \SI{14}{\day} as counted from the time of initial -seeding and activation. Cell counts and viability were assessed using -\product{trypan blue}{\thermo}{T10282} or \product{\gls{aopi}}{Nexcelom - Bioscience}{CS2-0106-5} and a \product{Countess Automated Cell Counter}{Thermo - Fisher}{Countess 3 FL}. Media was added to cultures every \SIrange{2}{3}{\day} -depending on media color or a \SI{300}{\mg\per\deci\liter} minimum glucose -threshold. Media glucose was measured using a \product{GlucCell glucose - meter}{Chemglass}{CLS-1322-02}. +\SIrange{100}{400}{\IU\per\ml} \product{\gls{rhil2}}{Peprotech}{200-02} unless +otherwise noted. Cell cultures were expanded for \SI{14}{\day} as counted from +the time of initial seeding and activation. Cell counts and viability were +assessed using \product{trypan blue}{\thermo}{T10282} or +\product{\gls{aopi}}{Nexcelom Bioscience}{CS2-0106-5} and a \product{Countess + Automated Cell Counter}{Thermo Fisher}{Countess 3 FL}. Media was added to +cultures every \SIrange{2}{3}{\day} depending on media color or a +\SI{300}{\mg\per\deci\liter} minimum glucose threshold. Media glucose was +measured using a \product{GlucCell glucose meter}{Chemglass}{CLS-1322-02}. Cells on the \glspl{dms} were visualized by adding \SI{0.5}{\ul} \product{\gls{stppe}}{\bl}{405204} and \SI{2}{ul} @@ -1406,19 +1400,20 @@ Cells on the \glspl{dms} were visualized by adding \SI{0.5}{\ul} imaging on a spinning disk confocal microscope. In the case of Grex bioreactors, we either used a \product{24 well plate}{Wilson - Wolf}{P/N 80192M} or a \product{6 well plate}{P/N 80240M}. + Wolf}{P/N 80192M} or a \product{6 well plate}{Wilson Wolf}{P/N 80240M}. \subsection{Quantifying cells on DMS interior} % TODO add a product number to MTT (if I can find it) -Cells were stained and visualized using \gls{mtt}. \glspl{dms} with attached and -loosely attached cells were sampled as desired and filtered through a -\SI{40}{\um} cell strainer. While still in the cell strainer, \glspl{dms} were -washed twice with \gls{pbs} and then dried by pulling liquid through the bottom -of the cell strainer via a micropipette and dabbing with a KimWipe. \glspl{dms} -were transferred to a 24 well plate with \SI{400}{\ul} media. \SI{40}{\ul} -\gls{mtt} was added to each well and allowed to incubate for \SI{3}{\hour}, -after which \glspl{dms} with cell were visualized via a brightfield microscope. +To visualize T cells on the interior of the \glspl{dms}, we stained them with +\gls{mtt}. \glspl{dms} with attached and loosely attached cells were sampled as +desired and filtered through a \SI{40}{\um} cell strainer. While still in the +cell strainer, \glspl{dms} were washed twice with \gls{pbs} and then dried by +pulling liquid through the bottom of the cell strainer via a micropipette and +dabbing with a KimWipe. \glspl{dms} were transferred to a 24 well plate with +\SI{400}{\ul} media. \SI{40}{\ul} \gls{mtt} was added to each well and allowed +to incubate for \SI{3}{\hour}, after which \glspl{dms} with cell were visualized +via a brightfield microscope. To quantify cells on the interior of \glspl{dms}, cells and \glspl{dms} were isolated analogously to those for the \gls{mtt} stain up until the drying step. @@ -1433,13 +1428,13 @@ Apoptosis was quantified using \gls{anv} according to the manufacturer's instructions. Briefly, cells were transferred to flow tubes and washed twice with \gls{pbs} by adding \SI{3}{\ml} to each tube, centrifuging for \SI{400}{\gforce}, and aspirating the liquid down to \SI{200}{\ul}. The cells -were analogously washed a third time with staining buffer (\SI{10}{\mM} HEPES, -\SI{140}{\mM} NaCl, \SI{2.5}{\mM} CaCl\textsubscript{2}) and aspirated down to a -final volume of \SI{100}{\ul}. Cells were stained in this volume with +were analogously washed a third time with staining buffer (\SI{10}{\mM} +\gls{hepes}, \SI{140}{\mM} NaCl, \SI{2.5}{\mM} \ce{CaCl2}) and aspirated down to +a final volume of \SI{100}{\ul}. Cells were stained in this volume with \SI{1}{\ul} \product{\gls{anv}-\gls{fitc}}{\bl}{640906} and \SI{5}{\ul} -\product{\gls{pi}}{\thermo}{P3566} and incubated for \SI{15}{\minute} at gls{rt} -in the dark. After incubation, \SI{400}{\ul} staining buffer was added to each -tube. Each tube was then analyzed via flow cytometry. +\product{\gls{pi}}{\thermo}{P3566} and incubated for \SI{15}{\minute} at +\gls{rt} in the dark. After incubation, \SI{400}{\ul} staining buffer was added +to each tube. Each tube was then analyzed via flow cytometry. \subsection{quantification of Caspase-3/7} @@ -1453,13 +1448,13 @@ After incubation, cells were immediately analyzed via flow cytometry. \Gls{bcl2} was quantified using an \product{Human Total Bcl-2 DuoSet \gls{elisa} kit}{Rnd Systems}{DYC827B-2} according to the manufacturer's instructions and -supplemented with \product{5X diluent buffer}{\bl}{421203}, \product{\gls{tmb} - substrate solution}{eBioscience}{00-4201-56}, and \SI{2}{\normal} -H\textsubscript{2}SO\textsubscript{4} stop solution made in house. Briefly, -cells were lysed using \product{10X lysis buffer}{Cell Signaling}{9803S}, and -the lysate was quantified for protein using a \product{\gls{bca} - assay}{\thermo}{23225} as directed. Standardized lysates were measured using -the \gls{elisa} kit as directed. +supplemented with \product{\gls{tmb} substrate + solution}{eBioscience}{00-4201-56}, \product{5X diluent buffer}{\bl}{421203}, +and \SI{2}{\normal} \ce{H2SO4} stop solution made in house. Briefly, cells were +lysed using \product{10X lysis buffer}{Cell Signaling}{9803S}, and the lysate +was quantified for protein using a \product{\gls{bca} assay}{\thermo}{23225} as +directed. Standardized lysates were measured using the \gls{elisa} kit as +directed. \subsection{chemotaxis assay} @@ -1479,24 +1474,30 @@ transwell was quantified for total cells using \product{countbright Cytotoxicity of expanded \gls{car} T cells was assessed using a degranulation assay as previously described\cite{Schmoldt1975}. Briefly, \num{3e5} T cells were incubated with \num{1.5e5} target cells consisting of either \product{K562 -wild type cells}{ATCC}{CCL-243} or CD19- expressing K562 cells transformed + wild type cells}{ATCC}{CCL-243} or CD19- expressing K562 cells transformed with \gls{crispr} (kindly provided by Dr.\ Yvonne Chen, UCLA)\cite{Zah2016}. Cells were seeded in a flat bottom 96 well plate with \SI{1}{\ug\per\ml} -\product{\acd{49d}}{eBioscience}{16-0499-81}, \SI{2}{\micro\molar} \product{monensin}{eBioscience}{ -00-4505-51}, and \SI{1}{\ug\per\ml} \product{\acd{28}}{eBioscience}{302914} (all -functional grade \glspl{mab}) with \SI{250}{\ul} total volume. After -\SI{4}{\hour} incubation at \SI{37}{\degreeCelsius}, cells were stained for CD3, -CD4, and CD107a and analyzed on a BD LSR Fortessa. Readout was calculated as the -percent \cdp{107a} cells of the total \cdp{8} fraction. +\product{\acd{49d}}{eBioscience}{16-0499-81}, \SI{2}{\micro\molar} +\product{monensin}{eBioscience}{ 00-4505-51}, and \SI{1}{\ug\per\ml} +\product{\acd{28}}{eBioscience}{302914} (all functional grade \glspl{mab}) with +\SI{250}{\ul} total volume. After \SI{4}{\hour} incubation at +\SI{37}{\degreeCelsius}, cells were stained for CD3, CD4, and CD107a and +analyzed on a \bd{} LSR Fortessa. Readout was calculated as the percent +\cdp{107a} cells of the total \cdp{8} fraction. -\subsection{car expression} +\subsection{CAR expression} -\gls{car} expression was quantified as previously described\cite{Zheng2012}. -Briefly, cells were washed once and stained with \product{biotinylated - \gls{ptnl}}{\thermo}{29997}. After a subsequent wash, cells were stained with -\product{\gls{pe}-\gls{stp}}{\bl}{405204}, washed again, and analyzed on a -BD Accuri. Readout was percent \gls{pe}+ cells as compared to secondary controls -(\gls{pe}-\gls{stp} with no \gls{ptnl}). +\gls{car} expression of the \anti{CD19} \gls{car} was quantified as previously +described\cite{Zheng2012}. Briefly, cells were washed once and stained with +\product{biotinylated \gls{ptnl}}{\thermo}{29997}. After a subsequent wash, +cells were stained with \product{\gls{pe}-\gls{stp}}{\bl}{405204}, washed again, +and analyzed on a \bd{} Accuri. Readout was percent \gls{pe}+ cells as compared +to secondary controls (\gls{pe}-\gls{stp} with no \gls{ptnl}). + +\gls{car} expression of the \anti{\gls{bcma}} \gls{car} was quantified using a +\product{\gls{fitc}-labeled \gls{bcma} protein}{Acro}{Bca-hf254}. \SI{100}{\ng} +was added to tubes analogously to \gls{ptnl} and incubated for \SI{45}{\minute} +prior to analyzing on a \bd{} Accuri \subsection{car plasmid and lentiviral transduction} @@ -1527,39 +1528,37 @@ Kochenderfer at the NIH)\cite{Lam2020} was added to \SI{50}{\ul} \product{DH5$\upalpha$ cells}{\thermo}{18265017} and incubated for \SI{30}{\minute} on ice. The cell mixture was then heat-shocked at \SI{42}{\degreeCelsius} for \SI{20}{\minute} before being placed on ice for -another \SI{2}{\minute}. \SI{950}{\ul} \product{LB Broth}{TODO}{TODO} was added -to the cells which were then centrifuged for \SI{1}{\hour} at \SI{225}{\rpm}. -\SI{20}{\ul} of the cell mixture was then spread over selection plates and -incubated overnight at \SI{37}{\degreeCelsius}. Colonies were selected the -following day and incubated in \product{LB Broth}{TODO}{TODO} with -\product{ampicillin}{\sigald{}}{A9518-5G} at \SI{37}{\degreeCelsius} for -\SIrange{12}{16}{\hour} prior to using the \product{miniprep kit}{Qiagen}{27104} -as per the manufacturer's instructions to isolate the plasmid DNA. Transfer -plasmid along with \product{pMDLg/pRRE}{Addgene}{12251}, -\product{pRSV-Rev}{Addgene}{12253}, and \product{pMD2.G}{Addgene}{12259} -(generously provided by the Sloan lab at Emory University) in -\product{Opti-Mem}{\thermo}{31-985-070} with \product{lipfectamine - 2000}{\thermo}{11668019} were added dropwise to HEK 293T cells and incubated -for \SI{6}{\hour}, after which all media was replaced with fresh fresh media. -After \SI{24}{\hour} and \SI{48}{\hour}, supernatent was collected, pooled, and -concentrated using a \product{Lenti-X concentrator}{Takara}{631231} prior to -storing at \SI{-80}{\degreeCelsius}. +another \SI{2}{\minute}. \SI{950}{\ul} luria broth was added to the cells which +were then centrifuged for \SI{1}{\hour} at \SI{225}{\rpm}. \SI{20}{\ul} of the +cell mixture was then spread over selection plates and incubated overnight at +\SI{37}{\degreeCelsius}. Colonies were selected the following day and incubated +in luria broth with \product{ampicillin}{\sigald{}}{A9518-5G} at +\SI{37}{\degreeCelsius} for \SIrange{12}{16}{\hour} prior to using the +\product{miniprep kit}{Qiagen}{27104} as per the manufacturer's instructions to +isolate the plasmid DNA. Transfer plasmid along with +\product{pMDLg/pRRE}{Addgene}{12251}, \product{pRSV-Rev}{Addgene}{12253}, and +\product{pMD2.G}{Addgene}{12259} (generously provided by the Sloan lab at Emory +University) in \product{Opti-Mem}{\thermo}{31-985-070} with +\product{lipfectamine 2000}{\thermo}{11668019} were added dropwise to HEK 293T +cells and incubated for \SI{6}{\hour}, after which all media was replaced with +fresh fresh media. After \SI{24}{\hour} and \SI{48}{\hour}, supernatent was +collected, pooled, and concentrated using a \product{Lenti-X + concentrator}{Takara}{631231} prior to storing at \SI{-80}{\degreeCelsius}. \subsection{sulfo-NHS-biotin hydrolysis quantification} -The equation for hydrolysis of \gls{snb} was assumed to follow -\cref{chem:snb_hydrolysis}. +The equation for hydrolysis of \gls{snb} to biotin and \gls{nhs} is given by +\cref{chem:snb_hydrolysis}. -% TODO make this look prettier \begin{equation} \label{chem:snb_hydrolysis} \ce{NHS-CO-Biotin + OH- -> NHS- + Biotin-COOH} \end{equation} -The hydrolysis of \gls{snb} was performed spectroscopically. \gls{snb} was added -to either \gls{di} water or \gls{pbs} in a UV-transparent 96 well plate. Kinetic -analysis using a Biotech Plate Reader began immediately after prep, and readings -at \SI{260}{\nm} were taken every minute for \SI{2}{\hour}. +Measuring the hydrolysis of \gls{snb} was performed spectroscopically. \gls{snb} +was added to either \gls{di} water or \gls{pbs} in a UV-transparent 96 well +plate. Kinetic analysis using a BioTek plate reader began immediately after +prep, and readings at \SI{260}{\nm} were taken every minute for \SI{2}{\hour}. \subsection{reaction kinetics quantification} @@ -1568,41 +1567,44 @@ experimentally. \SI{40}{\ug\per\ml} \gls{stp} was added to multiple batches of biotin-coated microcarriers, and supernatents were taken at fixed intervals and quantified for \gls{stp} protein using the \gls{bca} assay. -% TODO defend why the microcarriers were saturated with stp -The effective diffusivity of the microcarriers was determined using a +The geometric diffusivity of the microcarriers was determined using a pseudo-steady-state model. Each microcarrier was assumed to be a porous sphere -with a fixed number of `\gls{stp} binding sites' equal to the number of -\gls{stp} molecules experimentally determined to bind to the microcarriers. -Because the reaction rate between biotin and \gls{stp} was so fast, we assumed -that the interface of free biotin shrunk as a function of \gls{stp} bound until -the center of the microcarriers was reached. We also assumed that the pores in -the microcarriers were large enough that the interactions between the \gls{stp} -and surfaces would be small, thus the apparent diffusivity could be represented -as a fraction of the diffusion coefficient of \gls{stp} in water. This model was -given by \cref{eqn:stp_diffusion_1,eqn:stp_diffusion_2}: +with a fixed number of uniformly distributed `\gls{stp} binding sites' equal to +the number of \gls{stp} molecules experimentally determined to bind to the +microcarriers. Because the reaction rate between biotin and \gls{stp} is so fast +(it is the strongest non-covalent bond in known existence), we assumed that the +interface of free biotin shrunk as a function of \gls{stp} diffusing to the +unbound biotin interface until the center of the microcarriers was reached. We +also assumed that the pores in the microcarriers were large enough that the +interactions between the \gls{stp} and surfaces would be small, thus the +geometric diffusivity could be represented as a fraction of the diffusion +coefficient of \gls{stp} in water. This model was given by +\cref{eqn:stp_diffusion_1,eqn:stp_diffusion_2}: % TODO actually derive these equations, eg state the initial conditions and % governing equation \begin{equation} \label{eqn:stp_diffusion_1} - \frac{dr}{dt} = \frac{-D_{app}C}{Br(1-r/R)} + \frac{dr}{dt} = \frac{-D_{app}C_b}{Br(1-r/R)} \end{equation} \begin{equation} \label{eqn:stp_diffusion_2} - \frac{dC}{dt} = \frac{-4 \pi n D_{app} C}{V(1/r-1/R)} + \frac{dC_b}{dt} = \frac{-4 \pi n D_{app} C_b}{V(1/r-1/R)} \end{equation} \noindent where \begin{itemize}[label={}] -\item $D_{app}$ is the apparent diffusion rate which is equal to $D_{STP}\beta$ -\item $D_{STP}$ the diffusion rate of \gls{stp} (or \glspl{mab} for later - calculations) in water +\item $D_{app}$ is the apparent diffusion rate of species $X$ which is equal to + $D\beta$ +\item $D$ the diffusion rate of species $X$ in water at room temperature + (where $X$ is \gls{stp} in this example and \glspl{mab} later in this section) \item $\beta$ a fractional parameter representing the tortuousity and void fraction of the microcarriers (here called the `geometric diffusivity') -\item $r$ is the interfatial radius of the unbound biotin within a microcarrier +\item $r$ is the interfatial radius of the unbound binding sites for species $X$ + within a microcarrier \item $t$ is the reaction time -\item $C$ is the concentration of \gls{stp} in the bulk solution +\item $C_b$ is the concentration of species $X$ in the bulk solution \item $V$ is the volume of the bulk medium \item $R$ is the average radius of the microcarriers \item $n$ is the number of microcarriers in the reaction volume @@ -1646,17 +1648,15 @@ partial differential equation and boundary conditions: \noindent where (in addition to the variables given already for \cref{eqn:stp_diffusion_1,eqn:stp_diffusion_2}) \begin{itemize}[label={}] -\item $N_i$ is the radial flux of the species in question inside the - microcarriers -\item $C_i$ is the concentration of the species in question inside the - microcarriers -\item $C_{i,0}$ is the initial concentration of the species in question inside +\item $N_i$ is the radial flux of species $X$ inside the microcarriers +\item $C_i$ is the concentration of species $X$ inside the microcarriers +\item $C_{i,0}$ is the initial concentration of species $X$ inside the microcarriers (which is assumed to be the concentration in the bulk before the wash volume is added) -\item $C_{b,0}$ is the initial bulk concentration of the species in question - outside the microcarriers after the initial wash volume has been added -\item $C_{b,\infty}$ is the final bulk concentration of the species in - question outside the microcarriers +\item $C_{b,0}$ is the initial bulk concentration of species $X$ outside the + microcarriers after the initial wash volume has been added +\item $C_{b,\infty}$ is the final bulk concentration of species $X$ outside the + microcarriers \end{itemize} Note that in order to avoid solving a moving boundary value problem, the @@ -1669,7 +1669,7 @@ concentration should change little. The same diffusion coefficients were used in determining the kinetics of the washing steps, and \SI{5.0e-6}{\cm\squared\per\second}\cite{Niether2020} was used as the diffusion coefficient for free biotin (which should be the only -species left in solution after all the \gls{snb} has hydrolyzed). +reactive species left in solution after all the \gls{snb} has hydrolyzed). All diffusion coefficients were taken to be valid at \gls{rt} and in \gls{di} water, which is a safe assumption given that our reaction medium was 1X @@ -1689,17 +1689,17 @@ thawed at \gls{rt} and vortexed to ensure homogeneity. To run the plate, \SI{25}{\ul} of magnetic beads were added to the plate and washed 3X using \SI{300}{\ul} of wash buffer. \SI{25}{\ul} of samples or standard were added to the plate and incubated for \SI{120}{\minute} at \SI{850}{\rpm} at \gls{rt} -before washing analogously 3X with wash. \SI{12.5}{\ul} detection \glspl{mab} -and \SI{25}{\ul} \gls{stppe} were sequentially added, incubated for +before washing analogously 3X with wash buffer. \SI{12.5}{\ul} detection +\glspl{mab} and \SI{25}{\ul} \gls{stppe} were sequentially added, incubated for \SI{30}{\minute} and vortexed, and washed analogously to the sample step. Finally, samples were resuspended in \SI{120}{\ul} reading buffer and analyzed -via a BioRad Bioplex 200 plate reader. An 8 point log2 standard curve was used, -and all samples were run with single replicates. +via a BioRad Bioplex 200 plate reader. An 8 point log\textsubscript{2} standard +curve was used, and all samples were run with single replicates. Luminex data was preprocessed using R for inclusion in downstream analysis as follows. Any cytokine level that was over-range (`OOR >' in output spreadsheet) was set to the maximum value of the standard curve for that cytokine. Any value -that was under-range (`OOR \SI{95}{\percent} complete}. +Using this geometric diffusivity and the known diffusion coefficient of a +\gls{mab} protein in water, we calculated the binding of \glspl{mab} per time +onto the microcarriers (this obviously assumes that the effectively diffusivity +is independent of the protein used, which should be reasonable given that the +pores of the microcarriers are huge compared to the proteins, and we don't +expect any significant reaction between the protein and the microcarrier surface +save for the \gls{stp}-biotin binding reaction). Once again, we used the maximum +number of \glspl{mab} observed to determine the number of `binding sites' for +\glspl{mab} on the microcarriers, which should correspond to the upper-bound for +the reaction time (\cref{fig:mab_coating}). According to this model, the +\gls{mab} binding reaction should be complete within \SI{75}{\minute} under the +conditions used for our protocol (\cref{fig:dms_mab_per_time})\footnote{We + actually used \SI{60}{\minute} as describe in the method section as this model + was not updated with new parameters until recently; however, we should point + out that even at \SI{60}{\minute} the reaction appears to be + >\SI{95}{\percent} complete}. Finally, we calculated the number of wash steps needed to remove the reagents between each step, including the time for each wash which required the geometric @@ -2024,9 +2022,11 @@ should not that the washing time for both the \gls{stp} and \gls{mab} coating steps were \SI{30}{\minute}, which is a significant margin of safety (albeit one that could be optimized). +MATLAB code and output for all the wash step calculations are given in +\cref{sec:appendix_washing}. + \subsection{DMSs can efficiently expand T cells compared to beads} -% FIGURE make sure the day on these is correct \begin{figure*}[ht!] \begingroup @@ -2038,10 +2038,11 @@ one that could be optimized). \caption[T cells growing on \glspl{dms}] {Cells grow in tight clusters in and around functionalized \gls{dms}. \subcap{fig:dms_cells_phase}{Phase-contrast image of T cells growing on - \glspl{dms} on day 7} + \glspl{dms}} \subcap{fig:dms_cells_fluor}{Confocal images of T cells in varying z-planes growing on \glspl{dms} on day 9. \Glspl{dms} were stained using \gls{stppe} (red) and T cells were stained using \acd{45}-\gls{af647}.} + Images are from day 7 of culture. } \label{fig:dms_cells} \end{figure*} @@ -2202,28 +2203,26 @@ harvested after \SI{14}{\day}) (\cref{tab:inside_regression}). After observing differences in expansion, we further hypothesized that the \gls{dms} cultures could lead to a different T cell phenotype. In particular, we -were interested in the formation of naïve and memory T cells, as these represent -a subset with higher replicative potential and therefore improved clinical -prognosis\cite{Gattinoni2011, Wang2018}. We measured naïve and memory T cell -frequency staining for CCR7 and CD62L (both of which are present on lower -differentiated T cells such as naïve, central memory, and stem memory -cells\cite{Gattinoni2012}). Using three donors, we noted again \glspl{dms} -produced more T cells over a \SI{14}{\day} expansion than beads, with -significant differences in number appearing as early after \SI{5}{\day} -(\cref{fig:dms_exp_fold_change}). Furthermore, we noted that \glspl{dms} -produced more memory/naïve cells after \SI{14}{\day} when compared to beads for -all donors (\cref{fig:dms_exp_mem,fig:dms_exp_cd4}) showing that the \gls{dms} -platform is able to selectively expand potent, early differentiation T cells. +were interested in the formation of \glspl{tn}, \gls{tscm}, and \glspl{tcm} as +these represent a subset with higher capacity to replicate and therefore +improved clinical prognosis\cite{Gattinoni2011, Wang2018}. We measured the +frequency of these subtypes by staining for CCR7 and CD62L. Using three donor +lots, we noted again \glspl{dms} produced more T cells over a \SI{14}{\day} +expansion than beads, with significant differences in number appearing as early +after \SI{5}{\day} (\cref{fig:dms_exp_fold_change}). Furthermore, we noted that +\glspl{dms} produced more memory/naïve cells after \SI{14}{\day} when compared +to beads for all donors (\cref{fig:dms_exp_mem,fig:dms_exp_cd4}) showing that +the \gls{dms} platform is able to selectively expand potent, early +differentiation T cells. Of additional interest was the preservation of the CD4+ compartment. In healthy donor samples (such as those used here), the typical CD4:CD8 ratio is 2:1. We noted that \glspl{dms} produced more CD4+ T cells than bead cultures as well as naïve/memory, showing that the \gls{dms} platform can selectively expand CD4 T -cells to a greater degree than beads (Figure 2c). The trends held true when -observing the CD4+ and CD8+ fractions of the naïve/memory subset (\ptmem{}) -(\cref{fig:dms_exp_mem4,fig:dms_exp_mem8}). +cells to a greater degree than beads \cref{fig:dms_exp_cd4}. The trends held +true when observing the CD4+ and CD8+ fractions of the naïve/memory subset +(\ptmem{}) (\cref{fig:dms_exp_mem4,fig:dms_exp_mem8}). -% FIGURE this figure has weird proportions % FIGURE this figure was not produced with the same donors as the figure above, % which is really confusing \begin{figure*}[ht!] @@ -2249,7 +2248,7 @@ experiments\footnote{these results were not always consistent, see the metaanalysis at the end of this aim for an in-depth quantification of this observation} that the fraction of \ptmem{} and \pth{} T cells was higher in the \gls{dms} groups compared to the bead groups (\cref{fig:dms_phenotype}). -This result was seen for multiple donors. We should not that in the case of +This result was seen for multiple donors. We should note that in the case of \pthp{}, the donors we used had an initial \pthp{} that was much higher (healthy donors generally have a CD4:CD8 ratio of 2:1), so the proper interpretation of this is that the \pthp{} decreases less over the culture period with the @@ -2267,12 +2266,13 @@ technology. After optimizing for naïve/memory and CD4 yield, we sought to determine if the \glspl{dms} were compatible with lentiviral transduction protocols used to -generate \gls{car} T cells27,28. We added a \SI{24}{\hour} transduction step on -day 1 of the \SI{14}{\day} expansion to insert an anti-CD19 \gls{car}29 and -subsequently measured the surface expression of the \gls{car} on day 14 -\cref{fig:car_production_flow_pl,fig:car_production_endpoint_pl}. We noted that -there was robust \gls{car} expression in over \SI{25}{\percent} of expanded T -cells, and there was no observable difference in \gls{car} expression between +generate \gls{car} T cells\cite{Tumaini2013, Lamers2014}. We added a +\SI{24}{\hour} transduction step on day 1 of the \SI{14}{\day} expansion to +insert an anti-CD19 \gls{car}\cite{Milone2009} and subsequently measured the +surface expression of the \gls{car} on day 14 +(\cref{fig:car_production_flow_pl,fig:car_production_endpoint_pl}). We noted +that there was robust \gls{car} expression in over \SI{25}{\percent} of expanded +T cells, and there was no observable difference in \gls{car} expression between beads and \glspl{dms}. We also verified the functionality of expanded \gls{car} T cells using a @@ -2283,8 +2283,8 @@ appearance of CD107a on CD8+ T cells. CD107a is found on the inner-surface of cytotoxic granules and will emerge on the surface after cytotoxic T cells are activated and degranulate. Indeed, we observed degranulation in T cells expanded with both beads and \glspl{dms}, although not to an observably different degree -\cref{fig:car_production_flow_degran,fig:car_production_endpoint_degran}. Taken -together, these results indicated that the \glspl{dms} provide similar +(\cref{fig:car_production_flow_degran,fig:car_production_endpoint_degran}). +Taken together, these results indicated that the \glspl{dms} provide similar transduction efficiency compared to beads. We also verified that expanded T cells were migratory using a chemotaxis assay @@ -2298,6 +2298,7 @@ T cells expanded using beads, but this interaction effect was only weakly significant (p = 0.068). No such effect was seen for \gls{dms}-expanded T cells, showing that migration was likely independent of \gls{car} transduction. +% FIGURE break this up to give the text more flexibility \begin{figure*}[ht!] \begingroup @@ -2391,8 +2392,8 @@ we did not move the T cells to a larger bioreactor as they grew in contrast with our plate cultures. This means that the cells had higher growth area constraints, which may have nullified any advantage to the expansion that we seen elsewhere (\cref{fig:dms_exp_fold_change}). Furthermore, the higher growth -area could mean higher signaling and higher differentiation rate to effector T -cells, which was why the \ptmemp{} was so low compared to other data +area could mean higher signaling and higher differentiation rate to +\glspl{teff}, which was why the \ptmemp{} was so low compared to other data (\cref{fig:dms_phenotype_mem}). \begin{figure*}[ht!] @@ -2466,7 +2467,7 @@ Since the aim of the analysis was to perform causal inference, we determined 6 possible treatment variables which we controlled when designing the experiments included in this dataset. Obviously the principle treatment parameter was ‘activation method’ which represented the effect of activating T cells with -either beads or our DMS method. We also included ‘bioreactor’ which was a +either beads or our \gls{dms} method. We also included ‘bioreactor’ which was a categorical for growing the T cells in a Grex bioreactor vs polystyrene plates, ‘feed criteria’ which represented the criteria used to feed the cells (using media color or a glucose meter), ‘IL2 Feed Conc’ as a continuous parameter for @@ -2477,11 +2478,11 @@ size of our dataset, so the only two parameters for which causal relationships could be evaluated were ‘activation method’ and ‘bioreactor’. We should also note that these were not the only set of theoretical treatment parameters that we could have used. For example, media feed rate is an important process -parameter, but this was dependent on the feeding criteria and the growth rate of -the cells, which in turn is determined by activation method. Therefore, ‘media -feed rate’ (or similar) is a ‘post-treatment parameter’ and would have violated -the backdoor criteria and severely biased our estimates of the treatment -parameters themselves. +parameter, but in our experiments this was dependent on the feeding criteria and +the growth rate of the cells, which in turn is determined by activation method. +Therefore, ‘media feed rate’ (or similar) is a ‘post-treatment parameter’ and +would have violated the backdoor criteria and severely biased our estimates of +the treatment parameters themselves. In addition to these treatment parameters, we also included covariates to improve the precision of our model. Among these were donor parameters including @@ -2548,43 +2549,43 @@ We then included all covariates and unbalanced treatment parameters and performed linear regression again (\cref{tab:ci_controlled,fig:metaanalysis_fx}). We observe that after controlling for additional noise, the models explained much more variability -($R^2$ between 0.76 and 0.87) and had relatively constant variance and small -deviations for normality as per the assumptions of regression analysis {Figure - X}. Furthermore, the coefficient for activation method in the case of fold -change changed very little but still remained quite high (note the -log-transformation) with \SI{143}{\percent} increase in fold change compared to -beads. Furthermore, the coefficient for \ptmemp{} dropped to about -\SI{2.7}{\percent} different and almost became non-significant at $\upalpha$ = -0.05, and the \dpthp{} response increased to almost a \SI{9}{\percent} difference -and became highly significant. Looking at the bioreactor treatment, we see that -using the bioreactor in the case of fold change and \ptmemp{} is actually harmful -to the response, while at the same time it seems to increase the \dpthp{} -response. We should note that this parameter merely represents whether or not -the choice was made experimentally to use a bioreactor or not; it does not -indicate why the bioreactor helped or hurt a certain response. For example, -using a Grex entails changing the cell surface and feeding strategy for the T -cells, and any one of these ‘mediating variables’ might actually be the cause of -the responses. +($R^2$ between 0.76 and 0.87). +% and had relatively constant variance and small +% deviations for normality as per the assumptions of regression analysis {Figure +% X}. +Furthermore, the coefficient for activation method in the case of fold change +changed very little but still remained quite high (note the log-transformation) +with \SI{143}{\percent} increase in fold change compared to beads. Furthermore, +the coefficient for \ptmemp{} dropped to a \SI{2.7}{\percent} increase and +almost became non-significant at $\upalpha$ = 0.05, and the \dpthp{} response +increased to almost a \SI{9}{\percent} increase and became highly significant. +Looking at the bioreactor treatment, we see that using the bioreactor in the +case of fold change and \ptmemp{} is actually harmful to the response, while at +the same time it seems to increase the \dpthp{} response. We should note that +this parameter merely represents whether or not the choice was made +experimentally to use a bioreactor or not; it does not indicate why the +bioreactor helped or hurt a certain response. For example, using a Grex entails +changing the cell surface and feeding strategy for the T cells, and any one of +these ‘mediating variables’ might actually be the cause of the responses. \section{discussion} % DISCUSSION this is fluffy -We have developed a T cell expansion system that recapitulates key features of -the in vivo lymph node microenvironment using DMSs functionalized with -activating mAbs. This strategy provided superior expansion with higher number of -naïve/memory and CD4+ T cells compared to state-of-the-art microbead technology -(Figure 2). Other groups have used biomaterials approaches to mimic the \invivo{} -microenvironment\cite{Cheung2018, Rio2018, Delalat2017, Lambert2017, Matic2013}; -however, to our knowledge this is the first system that specifically drives -naïve/memory and CD4+ T cell formation in a scalable, potentially -bioreactor-compatible manufacturing process. - -% DISCUSSION assuage krish by showing that in the isotype control fig that IL2 -% doesn't activation T cells: https://www.jimmunol.org/content/jimmunol/191/12/5822.full.pdf +We have developed a T cell expansion shows superior expansion with higher number +of naïve/memory and CD4+ T cells compared to state-of-the-art microbead +technology (\cref{fig:dms_exp}). Other groups have used biomaterials approaches +to mimic the \invivo{} microenvironment\cite{Cheung2018, Rio2018, Delalat2017, + Lambert2017, Matic2013}; however, to our knowledge this is the first system +that specifically drives naïve/memory and CD4+ T cell formation in a scalable, +potentially bioreactor-compatible manufacturing process. Given that the +isotype-control \glspl{mab} does not lead to expansion and that \il{2} does not +lead to expansion on its own (\cref{fig:dms_expansion_isotype}), we know that +the expansion of the T cells shown here is due to the \acd{3} and \acd{28} +\glspl{mab}\cite{Waysbort2013}. Memory and naïve T cells have been shown to be important clinically. Compared to -effectors, they have a higher proliferative capacity and are able to engraft for -months; thus they are able to provide long-term immunity with smaller +\glspl{teff}, they have a higher proliferative capacity and are able to engraft +for months; thus they are able to provide long-term immunity with smaller doses\cite{Gattinoni2012, Joshi2008}. Indeed, less differentiated T cells have led to greater survival both in mouse tumor models and human patients\cite{Fraietta2018, Adachi2018, Rosenberg2011}. Furthermore, clinical