ENH proofread most of aim 1
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tex/thesis.tex
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tex/thesis.tex
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@ -288,7 +288,10 @@
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\DeclareSIUnit\IU{IU}
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\DeclareSIUnit\IU{IU}
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\DeclareSIUnit\rpm{RPM}
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\DeclareSIUnit\rpm{RPM}
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\DeclareSIUnit\carrier{carrier}
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\DeclareSIUnit\carrier{carrier}
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\DeclareSIUnit\gauge{gauge}
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\DeclareSIUnit\dms{DMS}
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\DeclareSIUnit\dms{DMS}
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\DeclareSIUnit\stp{STP}
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\DeclareSIUnit\snb{SNB}
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\DeclareSIUnit\cell{cells}
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\DeclareSIUnit\cell{cells}
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\DeclareSIUnit\ab{mAb}
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\DeclareSIUnit\ab{mAb}
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\DeclareSIUnit\normal{N}
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\DeclareSIUnit\normal{N}
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@ -370,6 +373,7 @@
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\newcommand{\miltenyi}{Miltenyi Biotech}
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\newcommand{\miltenyi}{Miltenyi Biotech}
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\newcommand{\bl}{Biolegend}
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\newcommand{\bl}{Biolegend}
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\newcommand{\bd}{Becton Dickenson}
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\newcommand{\bd}{Becton Dickenson}
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\newcommand{\pltread}{BioTek plate reader}
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% the obligatory misc category
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% the obligatory misc category
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\newcommand{\inlinecode}{\texttt}
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\newcommand{\inlinecode}{\texttt}
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@ -1404,13 +1408,13 @@ novel considering the state-of-the-art technology for T cell manufacturing:
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\section{Introduction}
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\section{Introduction}
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The first aim was to develop a microcarrier system that mimics several key
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This aim was to develop a functionalized microcarrier system that mimics several
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aspects of the \invivo{} lymph node microenvironment. We compared compare this
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key aspects of the \invivo{} lymph node microenvironment. We compared compare
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system to state-of-the-art T cell activation technologies for both expansion
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this system to state-of-the-art T cell activation technologies for both
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potential and memory cell formation. The governing hypothesis was that
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expansion potential and memory cell formation. The governing hypothesis was that
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microcarriers functionalized with \acd{3} and \acd{28} \glspl{mab} will
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microcarriers functionalized with \acd{3} and \acd{28} \glspl{mab} will provide
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provide superior expansion and memory phenotype compared to state-of-the-art
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superior expansion and memory phenotype compared to state-of-the-art bead-based
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bead-based T cell expansion technology\footnote{adapted from \dmspaper{}}.
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T cell expansion technology\footnote{adapted from \dmspaper{}}.
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\section{Methods}
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\section{Methods}
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@ -1428,41 +1432,62 @@ bead-based T cell expansion technology\footnote{adapted from \dmspaper{}}.
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\end{figure*}
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\end{figure*}
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\product{\gls{cus}}{\gehc}{DG-2001-OO} or \product{\gls{cug}}{\gehc}{DG-0001-OO}
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\product{\gls{cus}}{\gehc}{DG-2001-OO} or \product{\gls{cug}}{\gehc}{DG-0001-OO}
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were suspended at \SI{20}{\mg\per\ml} in 1X \gls{pbs} and autoclaved. All
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were suspended at \SI{20}{\mg\per\ml} in 1X \gls{pbs} in a 15, 50, or 250
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subsequent steps were done aseptically, and all reactions were carried out at
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\si{\ml} conical tube. The mass of the tube with the \gls{pbs} and microcarriers
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\SI{20}{\mg\per\ml} carriers at room temperature and agitated using an orbital
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were recorded to the nearest millimeter (subsequently referred to here as
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shaker with a \SI{3}{\mm} orbit diameter. After autoclaving, the microcarriers
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``reaction mass''). The tube was centrifuged for \SI{30}{\second} at
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were washed using sterile \gls{pbs} three times in a 10:1 volume ratio.
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\SI{4500}{\gforce} to ensure all microcarriers were at the bottom of the tube.
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The tube was then autoclaved using a \SI{15}{\minute} cycle at
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\SI{121}{\degreeCelsius} and \SI{100}{\kPa\of{\gauge}}.
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All subsequent steps were done aseptically, and all reactions were carried out
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at \SI{20}{\mg\of{\carrier}\per\ml} at room temperature and agitated using an
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orbital shaker with a \SI{3}{\mm} orbit diameter. After autoclaving, the
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microcarriers were washed using sterile \gls{pbs} three times in a 10:1 volume
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ratio. The volume after these washes was corrected by massing the tube and its
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contents and adding or removing \gls{pbs} until the ``reaction mass'' was
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reached.
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\product{\Gls{snb}}{\thermo}{21217} was dissolved at approximately \SI{10}{\uM}
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\product{\Gls{snb}}{\thermo}{21217} was dissolved at approximately \SI{10}{\uM}
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in sterile ultrapure water, and the true concentration was then determined using
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in sterile ultrapure water, and the true concentration was then determined using
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the \gls{haba} assay (see below). \SI{5}{\ul\of{\ab}\per\mL} \gls{pbs} was added
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the \gls{haba} assay (see below). \SI{2.5}{\nmol\of{\snb}\per\mg\of{\carrier}}
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to carrier suspension and allowed to react for \SI{60}{\minute} at
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(unless otherwise noted) was added to carrier suspension and allowed to react
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\SI{700}{\rpm} of agitation. After the reaction, the amount of biotin remaining
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for \SI{60}{\minute} at \SI{700}{\rpm} of agitation. After the reaction, the
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in solution was quantified using the \gls{haba} assay (see below). The carriers
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amount of biotin attached to the microcarriers was determined indirectly by
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were then washed three times, which entailed adding sterile \gls{pbs} in a 10:1
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measuring the biotin in solution via the \gls{haba} assay (see below). The
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volumetric ratio, agitating at \SI{900}{\rpm} for \SI{10}{\minute}, adding up to
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carriers were then washed three times, which entailed adding sterile \gls{pbs}
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a 15:1 volumetric ratio (relative to reaction volume) of sterile \gls{pbs},
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in a 10:1 volumetric ratio, agitating at \SI{900}{\rpm} for \SI{10}{\minute},
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centrifuging at \SI{1000}{\gforce} for \SI{1}{\minute}, and removing all liquid
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adding up to a 15:1 volumetric ratio (relative to reaction volume) of sterile
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back down to the reaction volume.
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\gls{pbs}, centrifuging at \SI{1000}{\gforce} for \SI{1}{\minute}, and removing
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all liquid back down to the reaction volume. The volume of the \gls{pbs} was
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corrected by massing the tube and its contents and adding or removing \gls{pbs}
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until the tube mass matched the ``reaction mass.''
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To coat with \gls{stp}, \SI{40}{\ug\per\mL} \product{\gls{stp}}{Jackson
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To coat the microcarriers with \product{\gls{stp}}{Jackson
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Immunoresearch}{016-000-114} was added and allowed to react for
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Immunoresearch}{016-000-114}, \SI{2}{\ug\of{\stp}\per\mg\of{\carrier}} was
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\SI{60}{\minute} at \SI{700}{RPM} of agitation. After the reaction, supernatant
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added and allowed to react for \SI{60}{\minute} at \SI{700}{RPM} of agitation.
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was taken for the \product{\gls{bca} assay}{\thermo}{23225}, and the carriers
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After the reaction, \SI{400}{\ul} supernatant (regardless of tube size) was
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were washed analogously to the previous wash step to remove the biotin, except
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taken for the \product{\gls{bca} assay}{\thermo}{23225} in order to indirectly
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two washes were done and the agitation time was \SI{30}{\minute}. Biotinylated
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quantify \gls{stp} attachment. Prior to the assay, the supernatent was filtered
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through a \SI{40}{\um} cell strainer to remove any stray microcarriers, which
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could increase the \gls{bca} readout as the assay is protein-agnostic and each
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microcarrier is approximately \SI{1}{\ug}. The carriers were washed analogously
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to the previous wash step to remove biotin, except two wash cycles were used,
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the agitation time was \SI{30}{\minute}, and the first cycle had an extra
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\SI{400}{\ul} \gls{pbs} to make up for the volume removed for the \gls{bca}
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assay.
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To coat with \glspl{mab}, sterile \product{\gls{bsa}}{\sigald}{A9576} was first
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added to a final concentration of \SI{2}{\percent} in order to prevent
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non-specific binding of the \glspl{mab} to the reaction tubes. Biotinylated
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\glspl{mab} against human CD3 \catnum{\bl}{317320} and CD28 \catnum{\bl}{302904}
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\glspl{mab} against human CD3 \catnum{\bl}{317320} and CD28 \catnum{\bl}{302904}
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were combined in a 1:1 mass ratio and added to the carriers at
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were combined in a 1:1 mass ratio and added to the carriers at
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\SI{0.2}{\ug\of{\ab}\per\mg\of{\dms}}. Along with the \glspl{mab}, sterile
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\SI{0.2}{\ug\of{\ab}\per\mg\of{\carrier}}. \glspl{mab} were allowed to bind to
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\product{\gls{bsa}}{\sigald}{A9576} was added to a final concentration of
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the carriers for \SI{60}{\minute} with \SI{700}{\rpm} agitation. After binding,
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\SI{2}{\percent} in order to prevent non-specific binding of the antibodies to
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\SI{400}{\ul} supernatant was sampled to indirectly quantify \gls{mab}
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the reaction tubes. \glspl{mab} were allowed to bind to the carriers for
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attachment using an \product{\anti{\gls{igg}} \gls{elisa} kit}{Abcam}{157719}.
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\SI{60}{\minute} with \SI{700}{\rpm} agitation. After binding, supernatants were
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Fully functionalized \glspl{dms} were washed in sterile \gls{pbs} analogous to
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sampled to quantify remaining \gls{mab} concentration using an
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the previous washing step to remove excess \gls{stp}.
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\product{\anti{\gls{igg}} \gls{elisa} kit}{Abcam}{157719}. Fully functionalized
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\glspl{dms} were washed in sterile \gls{pbs} analogous to the previous washing
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step to remove excess \gls{stp}. They were washed once again in the cell culture
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media to be used for the T cell expansion.
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\begin{table}[!h] \centering
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\begin{table}[!h] \centering
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\caption{Microcarrier properties}
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\caption{Microcarrier properties}
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@ -1470,7 +1495,9 @@ media to be used for the T cell expansion.
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\input{../tables/carrier_properties.tex}
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\input{../tables/carrier_properties.tex}
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\end{table}
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\end{table}
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The concentration of the final \gls{dms} suspension was found by taking a
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Finished \glspl{dms} were washed once again in the cell culture media (analogous
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to previous washing steps) to be used for the T cell expansion. The
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concentration of the final \gls{dms} suspension was found by taking a
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\SI{50}{\uL} sample, plating in a well, and imaging the entire well. The image
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\SI{50}{\uL} sample, plating in a well, and imaging the entire well. The image
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was then manually counted to obtain a concentration. Surface area for
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was then manually counted to obtain a concentration. Surface area for
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\si{\ab\per\um\squared} was calculated using the properties for \gls{cus} and
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\si{\ab\per\um\squared} was calculated using the properties for \gls{cus} and
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@ -1486,25 +1513,28 @@ ester linkages from binding to the avidin proteins in the \gls{haba}/avidin
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premix. All quantifications of \gls{haba} were performed on an Eppendorf D30
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premix. All quantifications of \gls{haba} were performed on an Eppendorf D30
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Spectrophotometer using \product{\SI{70}{\ul} cuvettes}{BrandTech}{759200}. The
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Spectrophotometer using \product{\SI{70}{\ul} cuvettes}{BrandTech}{759200}. The
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extinction coefficient at \SI{500}{\nm} for \gls{haba}/avidin was assumed to be
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extinction coefficient at \SI{500}{\nm} for \gls{haba}/avidin was assumed to be
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\SI{34000}{\per\cm\per\molar}.
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\SI{34000}{\per\cm\per\molar}\footnote{\SI{500}{\nm} is normally used for the
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\gls{haba} assay, but the spectrophotometer to which we had access only had
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\SI{490}{\nm} as the closest wavelength; the extinction coefficient should
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change little}.
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The \gls{stp} binding to the microcarriers was quantified indirectly using a
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The \gls{stp} binding to the microcarriers was quantified indirectly using a
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\product{\gls{bca} kit}{\thermo}{23227} according to the manufacturer’s
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\product{\gls{bca} kit}{\thermo}{23227} according to the manufacturer’s
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instructions, with the exception that the standard curve was made with known
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instructions, with the exception that the standard curve was made with known
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concentrations of purified \gls{stp} instead of \gls{bsa}. Absorbance at
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concentrations of purified \gls{stp} instead of \gls{bsa}. Absorbance at
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\SI{592}{\nm} was quantified using a BioTek plate reader.
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\SI{592}{\nm} was quantified using a \pltread{}.
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The \gls{mab} binding to the microcarriers was quantified indirectly using an
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The \gls{mab} binding to the microcarriers was quantified indirectly using an
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\gls{elisa} assay per the manufacturer’s instructions, with the exception that
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\gls{elisa} assay per the manufacturer’s instructions, with the exception that
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the same \glspl{mab} used to coat the carriers were used as the standard for the
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the same \glspl{mab} used to coat the carriers were used as the standard for the
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\gls{elisa} standard curve.
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\gls{elisa} standard curve. This assay was quantified using a \pltread{}.
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Open biotin binding sites on the \glspl{dms} after \gls{stp} coating was
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Open biotin binding sites on the \glspl{dms} after \gls{stp} coating was
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quantified indirectly using \product{\gls{fitcbt}}{\thermo}{B10570}.
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quantified indirectly using \product{\gls{fitcbt}}{\thermo}{B10570}.
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Briefly, \SI{400}{\pmol\per\ml} \gls{fitcbt} were added to \gls{stp}-coated
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Briefly, \SI{400}{\pmol\per\ml} \gls{fitcbt} were added to \gls{stp}-coated
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carriers and allowed to react for \SI{20}{\minute} at room temperature under
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carriers and allowed to react for \SI{20}{\minute} at room temperature under
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constant agitation. The supernatant was quantified against a standard curve of
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constant agitation. The supernatant was quantified against a standard curve of
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\gls{fitcbt} using a BioTek plate reader.
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\gls{fitcbt} using a \pltread{}.
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\Gls{stp} binding was verified after the \gls{stp}-binding step visually by
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\Gls{stp} binding was verified after the \gls{stp}-binding step visually by
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adding \gls{fitcbt} to the \gls{stp}-coated \glspl{dms}, resuspending in
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adding \gls{fitcbt} to the \gls{stp}-coated \glspl{dms}, resuspending in
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@ -1523,7 +1553,7 @@ Cryopreserved primary human T cells were either obtained as sorted
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using \glspl{dms} or \product{\SI{3.5}{\um} CD3/CD28 magnetic
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using \glspl{dms} or \product{\SI{3.5}{\um} CD3/CD28 magnetic
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beads}{\miltenyi}{130-091-441}. In the case of beads, T cells were activated
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beads}{\miltenyi}{130-091-441}. In the case of beads, T cells were activated
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at the manufacturer recommended cell:bead ratio of 2:1. In the case of
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at the manufacturer recommended cell:bead ratio of 2:1. In the case of
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\glspl{dms}, cells were activated using \SI{2500}{\dms\per\cm\squared} unless
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\glspl{dms}, cells were activated using \SI{1500}{\dms\per\cm\squared} unless
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otherwise noted. Initial cell density was \SIrange{2e6}{2.5e6}{\cell\per\ml} to
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otherwise noted. Initial cell density was \SIrange{2e6}{2.5e6}{\cell\per\ml} to
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in a 96 well plate with \SI{300}{\ul} volume. Serum-free media was either
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in a 96 well plate with \SI{300}{\ul} volume. Serum-free media was either
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\product{OpTmizer}{\thermo}{A1048501} or
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\product{OpTmizer}{\thermo}{A1048501} or
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@ -1616,9 +1646,9 @@ transwell was quantified for total cells using \product{countbright
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Cytotoxicity of expanded \gls{car} T cells was assessed using a degranulation
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Cytotoxicity of expanded \gls{car} T cells was assessed using a degranulation
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assay as previously described\cite{Schmoldt1975}. Briefly, \num{3e5} T cells
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assay as previously described\cite{Schmoldt1975}. Briefly, \num{3e5} T cells
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were incubated with \num{1.5e5} target cells consisting of either \product{K562
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were incubated with \num{1.5e5} target cells consisting of either \product{K562
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wild type cells}{ATCC}{CCL-243} or CD19- expressing K562 cells transformed
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wild type cells}{ATCC}{CCL-243} or \cdp{19} K562 cells transformed with
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with \gls{crispr} (kindly provided by Dr.\ Yvonne Chen, UCLA)\cite{Zah2016}.
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\gls{crispr} (kindly provided by Dr.\ Yvonne Chen, UCLA)\cite{Zah2016}. Cells
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Cells were seeded in a flat bottom 96 well plate with \SI{1}{\ug\per\ml}
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were seeded in a flat bottom 96 well plate with \SI{1}{\ug\per\ml}
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\product{\acd{49d}}{eBioscience}{16-0499-81}, \SI{2}{\micro\molar}
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\product{\acd{49d}}{eBioscience}{16-0499-81}, \SI{2}{\micro\molar}
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\product{monensin}{eBioscience}{ 00-4505-51}, and \SI{1}{\ug\per\ml}
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\product{monensin}{eBioscience}{ 00-4505-51}, and \SI{1}{\ug\per\ml}
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\product{\acd{28}}{eBioscience}{302914} (all functional grade \glspl{mab}) with
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\product{\acd{28}}{eBioscience}{302914} (all functional grade \glspl{mab}) with
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@ -1643,23 +1673,24 @@ prior to analyzing on a \bd{} Accuri
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\subsection{CAR Plasmid and Lentiviral Transduction}
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\subsection{CAR Plasmid and Lentiviral Transduction}
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The anti-CD19-CD8-CD137-CD3$\upzeta$ \gls{car} with the EF1$\upalpha$
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The anti-CD19-CD8-CD137-CD3$\upzeta$ \gls{car} sequence with the EF1$\upalpha$
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promotor\cite{Milone2009} was synthesized (Aldevron) and subcloned into a
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promotor\cite{Milone2009} was synthesized (Aldevron) and subcloned into a
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\product{FUGW}{Addgene}{14883} kindly provided by the Emory Viral Vector Core.
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\product{FUGW transfer plasmid}{Addgene}{14883} kindly provided by the Emory
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Lentiviral vectors were synthesized by the Emory Viral Vector Core or the
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Viral Vector Core. Lentiviral vectors were synthesized by the Emory Viral Vector
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Cincinnati Children's Hospital Medical Center Viral Vector Core. RNA titer was
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Core or the Cincinnati Children's Hospital Medical Center Viral Vector Core. RNA
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calculated using a \product{Lenti-X \gls{qpcr} titer kit}{Takara}{631235}. To
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titer was calculated using a \product{Lenti-X \gls{qpcr} titer
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transduce primary human T cells, \product{retronectin}{Takara}{T100A} was coated
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kit}{Takara}{631235}. To transduce primary human T cells,
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onto non-TC treated 96 well plates and used to immobilize lentiviral vector
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\product{retronectin}{Takara}{T100A} was coated onto non-TC treated 96 well
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particles according to the manufacturer's instructions. Briefly, retronectin
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plates and used to immobilize lentiviral vector particles according to the
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solution was adsorbed overnight at \SI{4}{\degreeCelsius} and blocked the next
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manufacturer's instructions. Briefly, retronectin solution was adsorbed
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day using \gls{bsa}. Prior to transduction, lentiviral supernatant was
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overnight at \SI{4}{\degreeCelsius} and blocked the next day using \gls{bsa}.
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spinoculated at \SI{2000}{\gforce} for \SI{2}{\hour} at \SI{4}{\degreeCelsius}.
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Prior to transduction, lentiviral supernatant was spinoculated at
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T cells were activated in 96 well plates using beads or \glspl{dms} for
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\SI{2000}{\gforce} for \SI{2}{\hour} at \SI{4}{\degreeCelsius}. T cells were
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\SI{24}{\hour}, and then cells and beads/\glspl{dms} were transferred onto
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activated in 96 well plates using beads or \glspl{dms} for \SI{24}{\hour}, and
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lentiviral vector coated plates and incubated for another \SI{24}{\hour}. Cells
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then cells and beads/\glspl{dms} were transferred onto lentiviral vector coated
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and beads/\glspl{dms} were removed from the retronectin plates using vigorous
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plates and incubated for another \SI{24}{\hour}. Cells and beads/\glspl{dms}
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pipetting and transferred to another 96 well plate wherein expansion continued.
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were removed from the retronectin plates using vigorous pipetting and
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transferred to another 96 well plate wherein expansion continued.
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% METHOD fill in missing product numbers
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% METHOD fill in missing product numbers
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\gls{bcma} \gls{car} lentiviral vector was synthesized in house as
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\gls{bcma} \gls{car} lentiviral vector was synthesized in house as
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@ -1697,19 +1728,36 @@ The equation for hydrolysis of \gls{snb} to biotin and \gls{nhs} is given by
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\ce{NHS-CO-Biotin + OH- -> NHS- + Biotin-COOH}
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\ce{NHS-CO-Biotin + OH- -> NHS- + Biotin-COOH}
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||||||
\end{equation}
|
\end{equation}
|
||||||
|
|
||||||
Measuring the hydrolysis of \gls{snb} was performed spectroscopically. \gls{snb}
|
Measuring the hydrolysis of \gls{snb} was performed spectroscopically as the
|
||||||
was added to either \gls{di} water or \gls{pbs} in a UV-transparent 96 well
|
extinction coefficient of \ce{NHS-} is well-known. \gls{snb} was added to either
|
||||||
plate. Kinetic analysis using a BioTek plate reader began immediately after
|
\gls{di} water or \gls{pbs} in a UV-transparent 96 well plate. Kinetic analysis
|
||||||
prep, and readings at \SI{260}{\nm} were taken every minute for \SI{2}{\hour}.
|
using a \pltread{} began immediately after prep, and readings at \SI{260}{\nm}
|
||||||
|
were taken every minute for \SI{2}{\hour}. The extinction coefficient of
|
||||||
|
\ce{NHS-} at \SI{260}{\nm} was assumed to be \SI{8600}{\per\cm\per\molar}.
|
||||||
|
|
||||||
\subsection{Reaction Kinetics Quantification}
|
\subsection{Reaction Kinetics Quantification}
|
||||||
|
|
||||||
The diffusion of \gls{stp} into biotin-coated microcarriers was determined
|
The reaction kinetics of \gls{stp} attaching to biotin-coated microcarriers was
|
||||||
experimentally. \SI{40}{\ug\per\ml} \gls{stp} was added to multiple batches of
|
determined experimentally. \SI{40}{\ug\per\ml} \gls{stp} was added to multiple
|
||||||
biotin-coated microcarriers, and supernatents were taken at fixed intervals and
|
batches of biotin-coated microcarriers, and supernatents were taken at fixed
|
||||||
quantified for \gls{stp} protein using the \gls{bca} assay.
|
intervals and quantified for \gls{stp} protein using the \gls{bca} assay as
|
||||||
|
described above.
|
||||||
|
|
||||||
The geometric diffusivity of the microcarriers was determined using a
|
To model diffusion in the microcarriers, we assumed that its pores were large
|
||||||
|
enough that the interactions between the \gls{stp} and surfaces would be small.
|
||||||
|
This means that the apparent, macroscropic diffusion of a given species within
|
||||||
|
the microcarriers would only depend on the aqueous diffusion coefficient of
|
||||||
|
\gls{stp} and a fractional factor (the ``geometric diffusivity'') representing
|
||||||
|
the additional path length an \gls{stp} molecule would take in the microcarriers
|
||||||
|
due to the tortuousity and void fraction of its pore network. This is given in
|
||||||
|
\cref{eqn:stp_diffusion_3}.
|
||||||
|
|
||||||
|
\begin{equation}
|
||||||
|
\label{eqn:stp_diffusion_3}
|
||||||
|
\gls{sym:appdiff}=\gls{sym:diff} \gls{sym:geodiff}
|
||||||
|
\end{equation}
|
||||||
|
|
||||||
|
This geometric diffusivity of the microcarriers was determined using a
|
||||||
pseudo-steady-state model. Each microcarrier was assumed to be a porous sphere
|
pseudo-steady-state model. Each microcarrier was assumed to be a porous sphere
|
||||||
with a fixed number of uniformly distributed ``receptors'' equal to the number
|
with a fixed number of uniformly distributed ``receptors'' equal to the number
|
||||||
of \gls{stp} molecules (here called ``ligands'') experimentally determined to
|
of \gls{stp} molecules (here called ``ligands'') experimentally determined to
|
||||||
|
@ -1717,11 +1765,8 @@ 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),
|
\gls{stp} is so fast (it is the strongest non-covalent bond in known existence),
|
||||||
we assumed that the interface of unbound receptors (free biotin) shrunk as a
|
we assumed that the interface of unbound receptors (free biotin) shrunk as a
|
||||||
function of \gls{stp} diffusing to the unbound biotin interface until the center
|
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
|
of the microcarriers was reached. This model was given by
|
||||||
microcarriers were large enough that the interactions between the \gls{stp} and
|
\cref{eqn:stp_diffusion_1,eqn:stp_diffusion_2}:
|
||||||
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,eqn:stp_diffusion_3}:
|
|
||||||
|
|
||||||
\begin{equation}
|
\begin{equation}
|
||||||
\label{eqn:stp_diffusion_1}
|
\label{eqn:stp_diffusion_1}
|
||||||
|
@ -1738,24 +1783,22 @@ given by \cref{eqn:stp_diffusion_1,eqn:stp_diffusion_2,eqn:stp_diffusion_3}:
|
||||||
{\gls{sym:vol} (1 / \gls{sym:rad} - 1 / \gls{sym:mcrad})}
|
{\gls{sym:vol} (1 / \gls{sym:rad} - 1 / \gls{sym:mcrad})}
|
||||||
\end{equation}
|
\end{equation}
|
||||||
|
|
||||||
\begin{equation}
|
|
||||||
\label{eqn:stp_diffusion_3}
|
|
||||||
\gls{sym:appdiff}=\gls{sym:diff} \gls{sym:geodiff}
|
|
||||||
\end{equation}
|
|
||||||
|
|
||||||
The diffusion rate of \gls{stp} was assumed to be
|
The diffusion rate of \gls{stp} was assumed to be
|
||||||
\SI{6.2e-7}{\cm\squared\per\second}\cite{Kamholz2001}. Since all but $\beta$ was
|
\SI{6.2e-7}{\cm\squared\per\second}\cite{Kamholz2001}. Since all but $\beta$ was
|
||||||
known, the experimental data was fit using these equations using
|
known, the experimental data was fit using these equations using
|
||||||
\inlinecode{ode45} in MATLAB and least squares as the fitting error. These
|
\inlinecode{ode45} in MATLAB and least squares as the fitting error. These
|
||||||
equations were then used analogously to describe the reaction profile of
|
fitted equations were then used to simulate the reaction profile of \glspl{mab}
|
||||||
\glspl{mab} assuming a diffusion rate of
|
assuming a diffusion rate of
|
||||||
\SI{4.8e-7}{\cm\squared\per\second}\cite{Sherwood1992}.
|
\SI{4.8e-7}{\cm\squared\per\second}\cite{Sherwood1992}.
|
||||||
|
|
||||||
To model the washing of the microcarriers, they once again were assumed to be
|
To model the washing of the microcarriers, they once again were assumed to be
|
||||||
porous spheres filled with whatever amount of reagent was left unbound from the
|
porous spheres filled with whatever amount of reagent was left unbound from the
|
||||||
previous step (which was assumed to be equal to concentration in the
|
previous step (which was assumed to be equal to concentration in the
|
||||||
supernatent). The diffusion out of the microcarriers is given by the following
|
supernatent). The fitted geometric diffusivity from above was used in these
|
||||||
partial differential equation and boundary conditions:
|
washing calculations, and \SI{5.0e-6}{\cm\squared\per\second}\cite{Niether2020}
|
||||||
|
was used as the diffusion coefficient for free biotin. The diffusion out of the
|
||||||
|
microcarriers is given by the following partial differential equation and
|
||||||
|
boundary conditions:
|
||||||
|
|
||||||
\begin{equation}
|
\begin{equation}
|
||||||
\label{eqn:stp_washing}
|
\label{eqn:stp_washing}
|
||||||
|
@ -1786,24 +1829,18 @@ partial differential equation and boundary conditions:
|
||||||
\evalat{\gls{sym:bulkligconc}}{\gls{sym:time} = \infty}) / 2
|
\evalat{\gls{sym:bulkligconc}}{\gls{sym:time} = \infty}) / 2
|
||||||
\end{equation}
|
\end{equation}
|
||||||
|
|
||||||
Note that in order to avoid solving a moving boundary value problem, the
|
In order to avoid solving a moving boundary value problem, the concentration at
|
||||||
concentration at the boundary of the microcarriers was fixed at the average of
|
the boundary of the microcarriers was fixed at the average of the final and
|
||||||
the final and initial concentration expected to be observed in bulk. This should
|
initial concentration expected to be observed in bulk. This should be a
|
||||||
be a reasonable assumption given that the volume inside the microcarriers is
|
reasonable assumption given that the volume inside the microcarriers is tiny
|
||||||
tiny compared to the amount of volume added in the wash, thus the boundary
|
compared to the amount of volume added in the wash, thus the boundary
|
||||||
concentration should change little.
|
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
|
|
||||||
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}
|
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
|
water, which is a safe assumption given that our reaction medium was 1X
|
||||||
\gls{pbs}.
|
\gls{pbs}. See \cref{sec:appendix_binding} and \cref{sec:appendix_washing} for
|
||||||
|
the MATLAB code and derivations, as well as output in the case of the washing
|
||||||
See \cref{sec:appendix_binding} and \cref{sec:appendix_washing} for the MATLAB
|
steps.
|
||||||
code and derivations, as well as output in the case of the washing steps.
|
|
||||||
|
|
||||||
\subsection{Luminex Analysis}\label{sec:luminex_analysis}
|
\subsection{Luminex Analysis}\label{sec:luminex_analysis}
|
||||||
|
|
||||||
|
@ -1850,23 +1887,22 @@ notebooks (eg OneNote files) was not easily parsable, and thus this data was
|
||||||
summarized in YAML files. The data included in these YAML files included reagent
|
summarized in YAML files. The data included in these YAML files included reagent
|
||||||
characteristics (vendor, catalog number, lot number, manufacturing date), cell
|
characteristics (vendor, catalog number, lot number, manufacturing date), cell
|
||||||
donor characteristics (age, \gls{bmi}, phenotype, demographic, gender), and all
|
donor characteristics (age, \gls{bmi}, phenotype, demographic, gender), and all
|
||||||
experimental parameters such as the number of bead or \gls{dms} added.
|
experimental parameters such as the number of beads or \glspl{dms} added.
|
||||||
|
|
||||||
To aggregate the data in a database, we wrote a program using Python, R, and
|
To aggregate the data in a database, we wrote a program using Python, R, and
|
||||||
Docker which retrieved the data from its source location and inserted the data
|
Docker which retrieved the data from its source location and inserted the data
|
||||||
in a Postgres database (specifically Aurora implementation hosted on \gls{aws}).
|
in a PostgreSQL database (specifically the Aurora implementation hosted on
|
||||||
This program included checks to ensure the integrity of source data (for
|
\gls{aws}). This program included checks to ensure the integrity of source data
|
||||||
example, flagging entries which had a reagent whose manufacturing date was after
|
(for example, flagging entries which had a reagent whose manufacturing date was
|
||||||
the date the experiment started, which signifies a human input error).
|
after the date the experiment started, which signifies a human input error).
|
||||||
|
|
||||||
|
|
||||||
\subsection{Statistical Analysis}\label{sec:statistics}
|
\subsection{Statistical Analysis}\label{sec:statistics}
|
||||||
|
|
||||||
For 1-way \gls{anova} analysis with Tukey multiple comparisons test,
|
For 1-way \gls{anova} analysis with Tukey multiple comparisons test,
|
||||||
significance was assessed using the \inlinecode{stat\_compare\_means} function
|
significance was assessed using the \inlinecode{stat\_compare\_means} function
|
||||||
with the \inlinecode{t.test} method from the \inlinecode{ggpubr} library in R.
|
with the \inlinecode{t.test} method from the \inlinecode{ggpubr} library in R.
|
||||||
For 2-way \gls{anova} analysis, the significance of main and interaction effects
|
For 2-way \gls{anova} analysis, significance of main and interaction effects
|
||||||
was determined using the car library in R.
|
was determined using the \inlinecode{car} library in R.
|
||||||
|
|
||||||
For least-squares linear regression, statistical significance was evaluated the
|
For least-squares linear regression, statistical significance was evaluated the
|
||||||
\inlinecode{lm} function in R. All results with categorical variables are
|
\inlinecode{lm} function in R. All results with categorical variables are
|
||||||
|
@ -1942,7 +1978,7 @@ properties of \gls{cus} and \gls{cug} were the same (\cref{tab:carrier_props}).
|
||||||
We chose to continue with the \gls{cus}-based \glspl{dms}, which showed higher
|
We chose to continue with the \gls{cus}-based \glspl{dms}, which showed higher
|
||||||
overall \gls{stp} binding compared to \gls{cug}-based \glspl{dms}
|
overall \gls{stp} binding compared to \gls{cug}-based \glspl{dms}
|
||||||
(\cref{fig:cug_vs_cus}). We showed that by varying the concentration of
|
(\cref{fig:cug_vs_cus}). We showed that by varying the concentration of
|
||||||
\gls{snb}, we were able to precisely control the amount of attached biotin
|
\gls{snb}, we were able to control the amount of attached biotin
|
||||||
(\cref{fig:biotin_coating}), mass of attached \gls{stp}
|
(\cref{fig:biotin_coating}), mass of attached \gls{stp}
|
||||||
(\cref{fig:stp_coating}), and mass of attached \glspl{mab}
|
(\cref{fig:stp_coating}), and mass of attached \glspl{mab}
|
||||||
(\cref{fig:mab_coating}). Furthermore, we showed that the microcarriers were
|
(\cref{fig:mab_coating}). Furthermore, we showed that the microcarriers were
|
||||||
|
@ -1995,7 +2031,7 @@ of reaction parameters on biotin binding. The parameters included in this
|
||||||
\gls{doe} were temperature, microcarrier mass, and \gls{snb} input mass. These
|
\gls{doe} were temperature, microcarrier mass, and \gls{snb} input mass. These
|
||||||
were parameters that we specifically controlled but hypothesized might have some
|
were parameters that we specifically controlled but hypothesized might have some
|
||||||
sensitivity on the final biotin mass attachment rate depending on their noise
|
sensitivity on the final biotin mass attachment rate depending on their noise
|
||||||
and uncertainty. In particular, temperature was `controlled' only by allowing
|
and uncertainty. In particular, temperature was ``controlled'' only by allowing
|
||||||
the microcarrier suspension to come to \gls{rt} after autoclaving. After
|
the microcarrier suspension to come to \gls{rt} after autoclaving. After
|
||||||
performing a full factorial \gls{doe} with three center points as the target
|
performing a full factorial \gls{doe} with three center points as the target
|
||||||
reaction conditions, we found that the final biotin binding mass is only highly
|
reaction conditions, we found that the final biotin binding mass is only highly
|
||||||
|
@ -2003,10 +2039,10 @@ dependent on biotin input concentration (\cref{fig:dms_qc_doe}). Overall,
|
||||||
temperature had no effect and carrier mass had no effect at higher temperatures,
|
temperature had no effect and carrier mass had no effect at higher temperatures,
|
||||||
but carrier mass had a slightly positive effect when temperature was low. This
|
but carrier mass had a slightly positive effect when temperature was low. This
|
||||||
could be because lower temperature might make spontaneous decay of \gls{snb}
|
could be because lower temperature might make spontaneous decay of \gls{snb}
|
||||||
occur slower, which would give \gls{snb} molecule more opportunity to diffuse
|
occur slower, which would give \gls{snb} molecules more opportunity to diffuse
|
||||||
into the microcarriers and react with amine groups to form attachments. It seems
|
into the microcarriers and react with amine groups to form attachments. It
|
||||||
that concentration only has a linear effect and doesn't interact with any of the
|
seemed that concentration only has a linear effect and doesn't interact with any
|
||||||
other variables, which is not surprisingly given the behavior observed in
|
of the other variables, which is not surprising given the behavior observed in
|
||||||
(\cref{fig:biotin_coating})
|
(\cref{fig:biotin_coating})
|
||||||
|
|
||||||
We also observed that the reaction pH does not influence the amount of biotin
|
We also observed that the reaction pH does not influence the amount of biotin
|
||||||
|
@ -2016,7 +2052,7 @@ it also increases the number of \ce{OH-} groups which can spontaneously
|
||||||
hydrolyze the \gls{snb} in solution (\cref{chem:snb_hydrolysis}).
|
hydrolyze the \gls{snb} in solution (\cref{chem:snb_hydrolysis}).
|
||||||
|
|
||||||
Furthermore, we observed that washing the microcarriers after autoclaving
|
Furthermore, we observed that washing the microcarriers after autoclaving
|
||||||
increases the biotin binding rate (\cref{fig:dms_qc_washes}). While we did not
|
increased the biotin binding rate (\cref{fig:dms_qc_washes}). While we did not
|
||||||
explore this further, one possible explanation for this behavior is that the
|
explore this further, one possible explanation for this behavior is that the
|
||||||
microcarriers have some loose protein in the form of powder or soluble peptides
|
microcarriers have some loose protein in the form of powder or soluble peptides
|
||||||
that competes for \gls{snb} binding against the surface of the microcarriers,
|
that competes for \gls{snb} binding against the surface of the microcarriers,
|
||||||
|
@ -2031,14 +2067,14 @@ carefully control the timing between \gls{snb} solution preparation and addition
|
||||||
to the microcarriers. We found that in the presence of \gls{di} water, \gls{snb}
|
to the microcarriers. We found that in the presence of \gls{di} water, \gls{snb}
|
||||||
is extremely stable (\cref{fig:dms_snb_decay_curves}) where it decays rapidly in
|
is extremely stable (\cref{fig:dms_snb_decay_curves}) where it decays rapidly in
|
||||||
the presence of \gls{pbs} buffered to pH of 7.1. In fact, the \gls{di} water
|
the presence of \gls{pbs} buffered to pH of 7.1. In fact, the \gls{di} water
|
||||||
curve actually decreases slightly, possibly due to \gls{snb} absorbing to the
|
curve actually decreased slightly, possibly due to \gls{snb} absorbing to the
|
||||||
plate surface. \gls{snb} is known to hydrolyze in the presence of \ce{OH-}, but
|
plate surface. \gls{snb} is known to hydrolyze in the presence of \ce{OH-}
|
||||||
the lack of hydrolysis in \gls{di} water can be explained by the fact that
|
groups, but the lack of hydrolysis in \gls{di} water can be explained by the
|
||||||
biotin itself is acidic, and thus the reaction is self-inhibitory in an
|
fact that biotin itself is acidic, and thus the reaction is self-inhibitory in
|
||||||
unbuffered and neutral pH system. Because we dissolve our \gls{snb} in \gls{di}
|
an unbuffered and neutral pH system. Because we dissolve our \gls{snb} in
|
||||||
water prior to adding it to the microcarrier suspension (which itself is in
|
\gls{di} water prior to adding it to the microcarrier suspension (which itself
|
||||||
\gls{pbs}) this result indicated that hydrolysis is not of concern when adding
|
is in \gls{pbs}) this result indicated that hydrolysis is not of concern when
|
||||||
\gls{snb} within minutes.
|
adding \gls{snb} within minutes.
|
||||||
|
|
||||||
\begin{figure*}[ht!]
|
\begin{figure*}[ht!]
|
||||||
\begingroup
|
\begingroup
|
||||||
|
@ -2078,7 +2114,7 @@ put in terms of fraction of input \gls{snb}, we observed that the curves are
|
||||||
almost identical (\cref{fig:dms_biotin_rxn_frac}). Given this, the reaction step
|
almost identical (\cref{fig:dms_biotin_rxn_frac}). Given this, the reaction step
|
||||||
for biotin attached can be set to \SI{30}{\minute}\footnote{we actually used
|
for biotin attached can be set to \SI{30}{\minute}\footnote{we actually used
|
||||||
\SI{60}{\minute} as outlined in methods, which shouldn't make any difference
|
\SI{60}{\minute} as outlined in methods, which shouldn't make any difference
|
||||||
except save for being excessive according to this result}.
|
except for costing more time}.
|
||||||
|
|
||||||
Next, we quantified the amount of \gls{stp} reacted with the surface of the
|
Next, we quantified the amount of \gls{stp} reacted with the surface of the
|
||||||
biotin-coated microcarriers. Different batches of biotin-coated \glspl{dms} were
|
biotin-coated microcarriers. Different batches of biotin-coated \glspl{dms} were
|
||||||
|
@ -2088,46 +2124,46 @@ using the \gls{bca} assay to indirectly quantify the amount of attached
|
||||||
(\cref{fig:dms_stp_per_time}). Assuming a quasi-steady-state paradigm, we used
|
(\cref{fig:dms_stp_per_time}). Assuming a quasi-steady-state paradigm, we used
|
||||||
this experimental binding data to compute the geometric diffusivity of the
|
this experimental binding data to compute the geometric diffusivity of the
|
||||||
microcarriers and fit a continuous model for the \gls{stp} binding reaction. We
|
microcarriers and fit a continuous model for the \gls{stp} binding reaction. We
|
||||||
computed the number of `binding sites' using the maximum mass observed to bind
|
computed the number of ``receptors'' using the maximum mass observed to bind
|
||||||
to the \gls{dms}, which should describe the upper-bound for reaction time
|
to the \gls{dms}, which should describe the upper-bound for reaction time
|
||||||
(\cref{fig:stp_coating}). Using the diffusion rate of the \gls{stp}
|
(\cref{fig:stp_coating}). Using the diffusion rate of the \gls{stp}
|
||||||
(\SI{6.2e-7}{\cm\squared\per\second}), we then calculated the geometric
|
(\SI{6.2e-7}{\cm\squared\per\second}), we then calculated the geometric
|
||||||
diffusivity of the microcarriers to be 0.190 (see
|
diffusivity of the microcarriers to be 0.190 (see
|
||||||
\cref{eqn:stp_diffusion_1,eqn:stp_diffusion_2}).
|
\cref{eqn:stp_diffusion_1,eqn:stp_diffusion_2}).
|
||||||
|
|
||||||
Using this geometric diffusivity and the known diffusion coefficient of a
|
Using this geometric diffusivity and the known diffusion coefficient of
|
||||||
\gls{mab} protein in water, we calculated the binding of \glspl{mab} per time
|
\glspl{mab} in water, we calculated the binding of \glspl{mab} per time onto the
|
||||||
onto the microcarriers (this obviously assumes that the effectively diffusivity
|
microcarriers (this obviously assumes that the effectively diffusivity is
|
||||||
is independent of the protein used, which should be reasonable given that the
|
independent of the protein used, which should be reasonable given that the pores
|
||||||
pores of the microcarriers are huge compared to the proteins, and we don't
|
of the microcarriers are huge compared to the proteins, and we don't expect any
|
||||||
expect any significant reaction between the protein and the microcarrier surface
|
significant reaction between the protein and the microcarrier surface save for
|
||||||
save for the \gls{stp}-biotin binding reaction). Once again, we used the maximum
|
the \gls{stp}-biotin binding reaction). Once again, we used the maximum number
|
||||||
number of \glspl{mab} observed to determine the number of `binding sites' for
|
of \glspl{mab} observed to determine the number of receptors for \glspl{mab} on
|
||||||
\glspl{mab} on the microcarriers, which should correspond to the upper-bound for
|
the microcarriers, which should correspond to the upper-bound for the reaction
|
||||||
the reaction time (\cref{fig:mab_coating}). According to this model, the
|
time (\cref{fig:mab_coating}). According to this model, the \gls{mab} binding
|
||||||
\gls{mab} binding reaction should be complete within \SI{75}{\minute} under the
|
reaction should be complete within \SI{75}{\minute} under the conditions used
|
||||||
conditions used for our protocol (\cref{fig:dms_mab_per_time})\footnote{We
|
for our protocol (\cref{fig:dms_mab_per_time})\footnote{we actually used
|
||||||
actually used \SI{60}{\minute} as describe in the method section as this model
|
\SI{60}{\minute} as describe in the method section as this model was not
|
||||||
was not updated with new parameters until recently; however, we should point
|
updated with new parameters until recently; however, we should point out that
|
||||||
out that even at \SI{60}{\minute} the reaction appears to be
|
even at \SI{60}{\minute} the reaction appears to be >\SI{95}{\percent}
|
||||||
>\SI{95}{\percent} complete}.
|
complete}.
|
||||||
|
|
||||||
Finally, we calculated the number of wash steps needed to remove the reagents
|
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
|
between each step, including the time for each wash which required the geometric
|
||||||
diffusivity of the microcarriers as calculated above. This is important, as
|
diffusivity of the microcarriers as calculated above. This is important, as
|
||||||
failing to wash out residual free \gls{snb} (for example) could occupy binding
|
failing to wash out residual free \gls{snb} (for example) could occupy binding
|
||||||
sites on the \gls{stp} molecules, lowering the effective binding capacity of the
|
sites on the \gls{stp} molecules, lowering the effective binding capacity of the
|
||||||
\gls{mab} downstream. Each wash was a 1:15 dilution (\SI{1}{\ml} reaction volume
|
\glspl{mab} downstream. Each wash was a 1:15 dilution (\SI{1}{\ml} reaction
|
||||||
in a \SI{15}{\ml} conical tube), and in the case of \gls{snb} we wished to wash
|
volume in a \SI{15}{\ml} conical tube), and in the case of \gls{snb} we wished
|
||||||
out enough biotin such that less than \SI{1}{\percent} of the binding sites in
|
to wash out enough biotin such that less than \SI{1}{\percent} of the binding
|
||||||
\gls{stp} would be occupied. Given this dilution factor, a maximum of
|
sites in \gls{stp} would be occupied. Given this dilution factor, a maximum of
|
||||||
\SI{20}{\nmol} of biotin remaining \cref{fig:biotin_coating} \SI{2.9}{\nmol}
|
\SI{20}{\nmol} of biotin remaining \cref{fig:biotin_coating} \SI{2.9}{\nmol}
|
||||||
biotin binding sites on \SI{40}{\ug} \gls{stp} (assuming 4 binding sites per
|
biotin binding sites on \SI{40}{\ug} \gls{stp} (assuming 4 binding sites per
|
||||||
\gls{stp} protein), this turned out to be 3 washes. By similar logic, using 2
|
\gls{stp} protein), this turned out to be 3 washes. By similar logic, using 2
|
||||||
washes after the \gls{stp} binding step will ensure that the number of free
|
washes after the \gls{stp} binding step will ensure that the number of free
|
||||||
\gls{stp} binding sites is less than 20X the number of \gls{mab} molecules
|
\gls{stp} binding sites is less than 20X the number of \gls{mab} molecules
|
||||||
added\footnote{This step may benefit from an additional wash, as the number of
|
added\footnote{This step may benefit from an additional wash, as the number of
|
||||||
washes used here was develop when \SI{40}{\ug} rather than \SI{4}{\ug}
|
washes used here was determined when \SI{40}{\ug} rather than \SI{4}{\ug}
|
||||||
\gls{mab} was used to coat the \gls{dms}, yielding a much wider margin.
|
\gls{mab} was used to coat the \gls{dms}, yielding a much wider margin.
|
||||||
However, it is also not clear to what extent this matters, as the \gls{mab}
|
However, it is also not clear to what extent this matters, as the \gls{mab}
|
||||||
have multiple biotin molecules per \gls{mab} protein, and thus one \gls{mab}
|
have multiple biotin molecules per \gls{mab} protein, and thus one \gls{mab}
|
||||||
|
@ -2140,15 +2176,15 @@ microcarriers to be porous spheres, this time with an initial concentration of
|
||||||
bulk concentration of the previous binding step, and calculated the amount of
|
bulk concentration of the previous binding step, and calculated the amount of
|
||||||
time it would take for the concentration profile inside the microcarriers to
|
time it would take for the concentration profile inside the microcarriers to
|
||||||
equilibrate to the bulk in the wash step. Using this model, we found that the
|
equilibrate to the bulk in the wash step. Using this model, we found that the
|
||||||
wash times for \gls{snb}, \gls{stp}, and \glspl{mab} was \SI{3}{\minute},
|
wash time for \gls{snb}, \gls{stp}, and \glspl{mab} was \SI{3}{\minute},
|
||||||
\SI{15}{\minute}, and \SI{17}{\minute} respectively. We verified that the
|
\SI{15}{\minute}, and \SI{17}{\minute} respectively. We verified that the
|
||||||
\gls{snb} was totally undetectable after washing (\cref{fig:dms_biotin_washed}).
|
\gls{snb} was totally undetectable after washing (\cref{fig:dms_biotin_washed}).
|
||||||
The other two species need to be verified in a similar manner; however, we
|
The other two species need to be verified in a similar manner; however, we
|
||||||
should not that the washing time for both the \gls{stp} and \gls{mab} coating
|
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
|
steps were \SI{30}{\minute}, which is a significant margin of safety (albeit one
|
||||||
one that could be optimized).
|
that could be optimized).
|
||||||
|
|
||||||
MATLAB code and output for all the wash step calculations are given in
|
MATLAB code and output for all wash step calculations are given in
|
||||||
\cref{sec:appendix_washing}.
|
\cref{sec:appendix_washing}.
|
||||||
|
|
||||||
\subsection{DMSs Can Efficiently Expand T Cells Compared to Beads}
|
\subsection{DMSs Can Efficiently Expand T Cells Compared to Beads}
|
||||||
|
@ -2195,18 +2231,17 @@ MATLAB code and output for all the wash step calculations are given in
|
||||||
We next sought to determine how our \glspl{dms} could expand T cells compared to
|
We next sought to determine how our \glspl{dms} could expand T cells compared to
|
||||||
state-of-the-art methods used in industry. All bead expansions were performed as
|
state-of-the-art methods used in industry. All bead expansions were performed as
|
||||||
per the manufacturer’s protocol, with the exception that the starting cell
|
per the manufacturer’s protocol, with the exception that the starting cell
|
||||||
densities were matched between the beads and carriers to
|
densities were matched between the beads and \glspl{dms} to
|
||||||
~\SI{2.5e6}{\cell\per\ml}. Throughout the culture we observed that T cells in
|
~\SI{2.5e6}{\cell\per\ml}. We observed that T cells in \gls{dms} culture grew in
|
||||||
\gls{dms} culture grew in tight clumps on the surface of the \glspl{dms} as well
|
tight clumps on the surface of the \glspl{dms} as well as inside the pores of
|
||||||
as inside the pores of the \glspl{dms}
|
the \glspl{dms} (\cref{fig:dms_cells_phase,fig:dms_cells_fluor}). Furthermore,
|
||||||
(\cref{fig:dms_cells_phase,fig:dms_cells_fluor}). Furthermore, we observed that
|
we observed that the \glspl{dms} conferred greater expansion compared to
|
||||||
the \glspl{dms} conferred greater expansion compared to traditional beads, and
|
traditional beads, and significantly greater expansion after \SI{12}{\day} of
|
||||||
significantly greater expansion after \SI{12}{\day} of culture
|
culture (\cref{fig:dms_expansion_bead}). We also observed no T cell expansion
|
||||||
(\cref{fig:dms_expansion_bead}). We also observed no T cell expansion using
|
using \glspl{dms} coated with an isotype control mAb compared to \glspl{dms}
|
||||||
\glspl{dms} coated with an isotype control mAb compared to \glspl{dms} coated
|
coated with \acd{3}/\acd{28} \glspl{mab} (\cref{fig:dms_expansion_isotype}),
|
||||||
with \acd{3}/\acd{28} \glspl{mab} (\cref{fig:dms_expansion_isotype}), confirming
|
confirming specificity of the expansion method. Given that \il{2} does not lead
|
||||||
specificity of the expansion method. Given that \il{2} does not lead to
|
to expansion on its own, we know that the expansion of the T cells shown here is
|
||||||
expansion on its own, we know that the expansion of the T cells shown here is
|
|
||||||
due to the \acd{3} and \acd{28} \glspl{mab}\cite{Waysbort2013}.
|
due to the \acd{3} and \acd{28} \glspl{mab}\cite{Waysbort2013}.
|
||||||
|
|
||||||
\begin{figure*}[ht!]
|
\begin{figure*}[ht!]
|
||||||
|
@ -2241,19 +2276,19 @@ usually present only on the cytoplasmic surface of the cell membrane, but flips
|
||||||
to the outside when the cell becomes apoptotic. \gls{pi} stains the nucleus of
|
to the outside when the cell becomes apoptotic. \gls{pi} stains the nucleus of
|
||||||
the cell, but only penetrates necrotic cells which have a perforated cell
|
the cell, but only penetrates necrotic cells which have a perforated cell
|
||||||
membrane. When staining for these two markers and assessing via flow cytometry,
|
membrane. When staining for these two markers and assessing via flow cytometry,
|
||||||
we observe that the \gls{dms}-expanded T cells have lower frequencies of
|
we observed that the \gls{dms}-expanded T cells have lower frequencies of
|
||||||
apoptotic and necrotic cells (\cref{fig:apoptosis_annV}). Furthermore, we
|
apoptotic and necrotic cells (\cref{fig:apoptosis_annV}). Furthermore, we
|
||||||
stained our cultures with CellEvent dye, which is an indicator of \gls{cas37},
|
stained our cultures with CellEvent dye, an indicator of \gls{cas37} which is
|
||||||
which is activated in apoptotic cells. In line with the \gls{pi}/\gls{anv}
|
activated in apoptotic cells. In line with the \gls{pi}/\gls{anv} results, we
|
||||||
results, we observed that the \gls{dms} T cells had lower frequency of
|
observed that the \gls{dms} T cells had lower frequency of \gls{cas37}
|
||||||
\gls{cas37} expression, indicating less apoptosis for our method
|
expression, indicating less apoptosis for our method (\cref{fig:apoptosis_cas}).
|
||||||
(\cref{fig:apoptosis_cas}). Finally, we lysed our cells and stained for
|
Finally, we lysed our cells and stained for \gls{bcl2}, which is also
|
||||||
\gls{bcl2}, which is also upregulated in apoptosis. In this case, some (but not
|
upregulated in apoptosis. In this case, some (but not all) of the bead-expanded
|
||||||
all) of the bead-expanded cultures showed higher \gls{bcl2} expression, which
|
cultures showed higher \gls{bcl2} expression, which could indicate more
|
||||||
could indicate more apoptosis in those groups (\cref{fig:apoptosis_bcl2}). None
|
apoptosis in those groups (\cref{fig:apoptosis_bcl2}). None of the \gls{dms}
|
||||||
of the \gls{dms} cultures showed similar heightened expression. Taken together,
|
cultures showed similar heightened expression. Taken together, these data
|
||||||
these data suggest that the \gls{dms} platform at least in part achieves higher
|
suggest that the \gls{dms} platform at least in part achieves higher expansion
|
||||||
expansion by lowering apoptosis of the cells in culture.
|
by lowering apoptosis.
|
||||||
|
|
||||||
\begin{figure*}[ht!]
|
\begin{figure*}[ht!]
|
||||||
\begingroup
|
\begingroup
|
||||||
|
@ -2281,19 +2316,19 @@ expansion by lowering apoptosis of the cells in culture.
|
||||||
\input{../tables/inside_fraction_regression.tex}
|
\input{../tables/inside_fraction_regression.tex}
|
||||||
\end{table}
|
\end{table}
|
||||||
|
|
||||||
We also asked how many cells were inside the \glspl{dms} vs. free-floating in
|
We also asked how many cells were inside the \glspl{dms} instead of
|
||||||
suspension and/or loosely attached to the surface. We qualitatively verified the
|
free-floating in suspension and/or loosely attached to the surface. We
|
||||||
presence of cells inside the \glspl{dms} using a \gls{mtt} stain to opaquely
|
qualitatively verified the presence of cells inside the \glspl{dms} using a
|
||||||
mark cells and enable visualization on a brightfield microscope
|
\gls{mtt} stain to opaquely mark cells and enable visualization on a brightfield
|
||||||
(\cref{fig:dms_inside_bf}). After seeding \glspl{dms} at different densities and
|
microscope (\cref{fig:dms_inside_bf}). After seeding \glspl{dms} at different
|
||||||
expanding for \SI{14}{\day}, we filtered the \glspl{dms} out of the cell
|
densities and expanding for \SI{15}{\day}, we filtered the \glspl{dms} out of
|
||||||
suspension and digested them using dispase to free any cells attached on the
|
the cell suspension and digested them using dispase to free any cells attached
|
||||||
inner surface. We observed that approximately \SI{15}{\percent} of the total
|
on the inner surface. We observed that approximately \SI{15}{\percent} of the
|
||||||
cells after \SI{14}{\day} were on the interior surface of the \glspl{dms}
|
total cells after \SI{15}{\day} were on the interior surface of the \glspl{dms}
|
||||||
(\cref{fig:dms_inside_regression,tab:inside_regression}). Performing linear
|
(\cref{fig:dms_inside_regression,tab:inside_regression}). Performing linear
|
||||||
regression on this data revealed that the percentage of T cells inside the
|
regression on this data revealed that the percentage of T cells inside the
|
||||||
\glspl{dms} does not depend on the initial starting cell density (at least when
|
\glspl{dms} does not depend on the initial starting cell density (at least when
|
||||||
harvested after \SI{14}{\day}) (\cref{tab:inside_regression}).
|
harvested after \SI{15}{\day}) (\cref{tab:inside_regression}).
|
||||||
|
|
||||||
\subsection{DMSs Lead to Greater Expansion and High-Quality Phenotypes}
|
\subsection{DMSs Lead to Greater Expansion and High-Quality Phenotypes}
|
||||||
|
|
||||||
|
@ -2332,7 +2367,7 @@ improved clinical prognosis\cite{Gattinoni2011, Wang2018}. We measured the
|
||||||
frequency of these subtypes by staining for CCR7 and CD62L. Using three donor
|
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}
|
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
|
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
|
as \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
|
\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
|
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
|
the \gls{dms} platform is able to selectively expand potent, early
|
||||||
|
@ -2364,25 +2399,23 @@ true when observing the CD4+ and CD8+ fractions of the naïve/memory subset
|
||||||
\label{fig:dms_phenotype}
|
\label{fig:dms_phenotype}
|
||||||
\end{figure*}
|
\end{figure*}
|
||||||
|
|
||||||
We also observed that, at least with the donors and conditions tested in these
|
We also observed that, at least among some donors and conditions\footnote{these
|
||||||
experiments\footnote{these results were not always consistent, see the
|
results were not always consistent, see the metaanalysis at the end of this
|
||||||
metaanalysis at the end of this aim for an in-depth quantification of this
|
aim for an in-depth quantification of this observation} that the fraction of
|
||||||
observation} that the fraction of \ptmem{} and \pth{} T cells was higher in
|
\ptmem{} and \pth{} T cells was higher in the \gls{dms} groups compared to the
|
||||||
the \gls{dms} groups compared to the bead groups
|
bead groups (\cref{fig:dms_phenotype})\footnote{these where not the same donors
|
||||||
(\cref{fig:dms_phenotype})\footnote{these where not the same donors as used for
|
as used for \cref{fig:dms_exp}}. Note that in the case of \pthp{}, the donors
|
||||||
\cref{fig:dms_exp}}. This result was seen for multiple donors. We should note
|
we used had an initial \pthp{} that was much higher (healthy donors generally
|
||||||
that in the case of \pthp{}, the donors we used had an initial \pthp{} that was
|
have a CD4:CD8 ratio of 2:1), so the proper interpretation of this is that the
|
||||||
much higher (healthy donors generally have a CD4:CD8 ratio of 2:1), so the
|
\pthp{} decreases less over the culture period with the \gls{dms} platform as
|
||||||
proper interpretation of this is that the \pthp{} decreases less over the
|
opposed to the beads (or alternatively, the \gls{dms} has less preferential
|
||||||
culture period with the \gls{dms} platform as opposed to the beads (or
|
expansion for \cdp{8} T cells). We cannot say the same about the \ptmemp{} since
|
||||||
alternatively, the \gls{dms} has less preferential expansion for CD8 T cells).
|
we did not have the initial data for this phenotype; (although memory and naive
|
||||||
We cannot say the same about the \ptmemp{} since we did not have the initial
|
cells should be the vast majority of cells given that \glspl{pbmc} is taken from
|
||||||
data for this phenotype; however (although it should be the vast majority of
|
blood which has mostly these cell types). Taken together, these data indicate
|
||||||
cells given that cryopreserved T cells from a healthy donor should generally be
|
the \gls{dms} platform has the capacity to expand higher numbers and percentages
|
||||||
composed of circulated memory and naive T cells). Taken together, these data
|
of highly potent \ptmem{} and \pth{} T cells compared to state-of-the-art bead
|
||||||
indicate the \gls{dms} platform has the capacity to expand higher numbers and
|
technology.
|
||||||
percentages of highly potent \ptmem{} and \pth{} T cells compared to
|
|
||||||
state-of-the-art bead technology.
|
|
||||||
|
|
||||||
\subsection{DMSs Produce Functional CAR T Cells}
|
\subsection{DMSs Produce Functional CAR T Cells}
|
||||||
|
|
||||||
|
@ -2390,12 +2423,12 @@ After optimizing for naïve/memory and CD4 yield, we sought to determine if the
|
||||||
\glspl{dms} were compatible with lentiviral transduction protocols used to
|
\glspl{dms} were compatible with lentiviral transduction protocols used to
|
||||||
generate \gls{car} T cells\cite{Tumaini2013, Lamers2014}. We added a
|
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
|
\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
|
insert an anti-CD19 \gls{car}\cite{Milone2009} with a \gls{moi} of 10 and
|
||||||
surface expression of the \gls{car} on day 14
|
subsequently measured the surface expression of the \gls{car} on day 14
|
||||||
(\cref{fig:car_cd19_flow,fig:car_cd19_endpoint}). We noted
|
(\cref{fig:car_cd19_flow,fig:car_cd19_endpoint}). We noted that there was robust
|
||||||
that there was robust \gls{car} expression in over \SI{25}{\percent} of expanded
|
\gls{car} expression in over \SI{25}{\percent} of expanded T cells, and there
|
||||||
T cells, and there was no observable difference in \gls{car} expression between
|
was no observable difference in \gls{car} expression between beads and
|
||||||
beads and \glspl{dms}.
|
\glspl{dms}.
|
||||||
|
|
||||||
We also verified the functionality of expanded \gls{car} T cells using a
|
We also verified the functionality of expanded \gls{car} T cells using a
|
||||||
degranulation assay\cite{Zheng2012}. Briefly, T cells were cocultured with
|
degranulation assay\cite{Zheng2012}. Briefly, T cells were cocultured with
|
||||||
|
@ -2451,7 +2484,7 @@ showing that migration was likely independent of \gls{car} transduction.
|
||||||
\caption[\acrshort{car} T Cell Functionality]
|
\caption[\acrshort{car} T Cell Functionality]
|
||||||
{\glspl{dms} produce functional \gls{car} T cells.
|
{\glspl{dms} produce functional \gls{car} T cells.
|
||||||
\subcap{fig:car_degran_flow}{Representative flow plot for
|
\subcap{fig:car_degran_flow}{Representative flow plot for
|
||||||
degenerating T cells.}
|
degranulating T cells.}
|
||||||
\subcap{fig:car_degran_endpoint}{Endpoint plots for transduced or
|
\subcap{fig:car_degran_endpoint}{Endpoint plots for transduced or
|
||||||
untransduced T cells stained with \cd{107a} for the degranulation assay.}
|
untransduced T cells stained with \cd{107a} for the degranulation assay.}
|
||||||
\subcap{fig:car_degran_migration}{Endpoint plot for transmigration assay
|
\subcap{fig:car_degran_migration}{Endpoint plot for transmigration assay
|
||||||
|
@ -2461,9 +2494,9 @@ showing that migration was likely independent of \gls{car} transduction.
|
||||||
\end{figure*}
|
\end{figure*}
|
||||||
|
|
||||||
In addition to CD19 \gls{car} T cells, we also demonstrated that the \gls{dms}
|
In addition to CD19 \gls{car} T cells, we also demonstrated that the \gls{dms}
|
||||||
platform can be used to expand \gls{car} T cells against \gls{bcma}. Analogously
|
platform can be used to expand \gls{car} T cells against \gls{bcma}. Analogous
|
||||||
to the case with CD19, \gls{dms} and bead produced similar fractions of \ptcar{}
|
to CD19, \gls{dms} and bead produced similar fractions of \ptcar{} cells (albeit
|
||||||
cells (albeit in this case at day 7 and with an undefined \gls{moi})
|
in this case at day 7 and with an undefined \gls{moi})
|
||||||
(\cref{fig:car_bcma_percent}). Also consistent with CD19 and non-\gls{car} data,
|
(\cref{fig:car_bcma_percent}). Also consistent with CD19 and non-\gls{car} data,
|
||||||
we also found that the number of \ptcar{} T cells was greater for \gls{dms} than
|
we also found that the number of \ptcar{} T cells was greater for \gls{dms} than
|
||||||
for bead (\cref{fig:car_bcma_total}).
|
for bead (\cref{fig:car_bcma_total}).
|
||||||
|
@ -2509,25 +2542,23 @@ for bead (\cref{fig:car_bcma_total}).
|
||||||
\label{fig:grex_results}
|
\label{fig:grex_results}
|
||||||
\end{figure*}
|
\end{figure*}
|
||||||
|
|
||||||
We also asked if the \gls{dms} platform could expand T cells in a static
|
We also asked if the \gls{dms} platform could expand T cells in a Grex
|
||||||
bioreactor such a Grex. We incubated T cells in a Grex analogously to that for
|
bioreactor. We incubated T cells in a Grex analogously to plates and found that
|
||||||
plates and found that T cells in Grex bioreactors expanded as efficiently as
|
T cells in Grex bioreactors expanded as efficiently as beads over \SI{14}{\day}
|
||||||
bead over \SI{14}{\day} and had similar viability
|
and had similar viability
|
||||||
(\cref{fig:grex_results_fc,fig:grex_results_viability}). Furthermore, consistent
|
(\cref{fig:grex_results_fc,fig:grex_results_viability}). Consistent with past
|
||||||
with past results, \glspl{dms}-expanded T cells had higher \pthp{} compared to
|
results, \glspl{dms}-expanded T cells had higher \pthp{} and \ptmemp{} compared
|
||||||
beads and higher \ptmemp{} compared to beads (\cref{fig:grex_mem,fig:grex_cd4}).
|
to beads (\cref{fig:grex_mem,fig:grex_cd4}). Overall the \ptmemp{} was lower
|
||||||
Overall the \ptmemp{} was much lower than that seen from cultures grown in
|
than that seen in standard plates (\cref{fig:dms_phenotype_mem}).
|
||||||
tissue-treated plates (\cref{fig:dms_phenotype_mem}).
|
|
||||||
|
|
||||||
These discrepancies might be explained in light of our other data as follows.
|
These discrepancies might be explained in light of other data as follows. The
|
||||||
The Grex bioreactor has higher media capacity relative to its surface area, and
|
Grex bioreactor has higher media capacity relative to its surface area, and we
|
||||||
we did not move the T cells to a larger bioreactor as they grew in contrast with
|
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
|
our plate cultures. This means that the cells had higher growth area
|
||||||
constraints, which may have nullified any advantage to the expansion that we
|
constraints, which may have nullified any advantage to the expansion seen in
|
||||||
seen elsewhere (\cref{fig:dms_exp_fold_change}). Furthermore, the higher growth
|
standard plates (\cref{fig:dms_exp_fold_change}). Furthermore, the higher growth
|
||||||
area could mean higher signaling and higher differentiation rate to
|
area could mean increased signaling and \gls{teff} differentiation, which was
|
||||||
\glspl{teff}, which was why the \ptmemp{} was so low compared to other data
|
why the \ptmemp{} was low compared to past data (\cref{fig:dms_phenotype_mem}).
|
||||||
(\cref{fig:dms_phenotype_mem}).
|
|
||||||
|
|
||||||
\begin{figure*}[ht!]
|
\begin{figure*}[ht!]
|
||||||
\begingroup
|
\begingroup
|
||||||
|
@ -2543,9 +2574,9 @@ area could mean higher signaling and higher differentiation rate to
|
||||||
We also quantified the cytokines released during the Grex expansion using
|
We also quantified the cytokines released during the Grex expansion using
|
||||||
Luminex. We noted that in nearly all cases, the \gls{dms}-expanded T cells
|
Luminex. We noted that in nearly all cases, the \gls{dms}-expanded T cells
|
||||||
released higher concentrations of cytokines compared to beads
|
released higher concentrations of cytokines compared to beads
|
||||||
(\cref{fig:grex_luminex}). This included higher concentrations of
|
(\cref{fig:grex_luminex}), including higher concentrations of pro-inflammatory
|
||||||
pro-inflammatory cytokines such as GM-CSF, \gls{ifng}, and \gls{tnfa}. This
|
cytokines such as GM-CSF, \gls{ifng}, and \gls{tnfa}. This demonstrates that
|
||||||
demonstrates that \gls{dms} could lead to more robust activation and fitness.
|
\glspl{dms} could lead to more robust activation.
|
||||||
|
|
||||||
Taken together, these data suggest that \gls{dms} also lead to robust expansion
|
Taken together, these data suggest that \gls{dms} also lead to robust expansion
|
||||||
in Grex bioreactors, although more optimization may be necessary to maximize the
|
in Grex bioreactors, although more optimization may be necessary to maximize the
|
||||||
|
|
Loading…
Reference in New Issue