diff --git a/tex/references.bib b/tex/references.bib index 900b615..5cc2809 100644 --- a/tex/references.bib +++ b/tex/references.bib @@ -2742,6 +2742,32 @@ CONCLUSIONS: We developed a simplified, semi-closed system for the initial selec publisher = {Elsevier {BV}}, } +@Article{Wang1984, + author = {James C. Wang}, + journal = {Journal of Materials Science}, + title = {Young{\textquotesingle}s modulus of porous materials}, + year = {1984}, + month = {mar}, + number = {3}, + pages = {801--808}, + volume = {19}, + doi = {10.1007/bf00540451}, + publisher = {Springer Science and Business Media {LLC}}, +} + +@Article{Ju2017, + author = {Lining Ju and Cheng Zhu}, + journal = {Biophysical Journal}, + title = {Benchmarks of Biomembrane Force Probe Spring Constant Models}, + year = {2017}, + month = {dec}, + number = {12}, + pages = {2842--2845}, + volume = {113}, + doi = {10.1016/j.bpj.2017.10.013}, + publisher = {Elsevier {BV}}, +} + @Comment{jabref-meta: databaseType:bibtex;} @Comment{jabref-meta: grouping: diff --git a/tex/thesis.tex b/tex/thesis.tex index f076c23..e93aea4 100644 --- a/tex/thesis.tex +++ b/tex/thesis.tex @@ -95,7 +95,7 @@ {\MakeUppercase{\chaptertitlename} \thechapter: }{0pt}{\uppercase} \titleformat{\section}[block]{\bfseries\large}{}{0pt}{\titlecap} \titleformat{\subsection}[block]{\itshape\large}{}{0pt}{\titlecap} -\titleformat{\subsubsection}[runin]{\bfseries\itshape\/}{}{0pt}{\titlecap} +\titleformat{\subsubsection}[runin]{\bfseries}{}{0pt}{\titlecap} \setlist[description]{font=$\bullet$~\textbf\normalfont} @@ -4574,16 +4574,94 @@ animal-origin concerns. Despite the improved outcomes in terms of expansion and phenotype relative to beads, we don't have a good understanding of why they \gls{dms} platform works -as well as it does. Several broad areas remain to be investigated, including the -role of the increased cytokine output (including \il{15} which was explored to -some extent in this work), the role of cells on the interior of the \gls{dms} -relative to those outside the \gls{dms}, and the role of the physical surface -properties of the \gls{dms} (including the morphology and the stiffness). One -plausible hypothesis to be tested is that the bumpy microcarrier surface is more -like that of an \gls{apc}, which enhances immunological synapse formation and -thus activation. Another related hypothesis is that the signal strength is -lower than the beads, which leads to increased proliferation, less exhaustion, -and by extension more memory. +as well as it does. The following are several plausible hypotheses and a +proposed experiment for testing them: + +\subsubsection{Cytokine Cross-talk} + +As hypothesized in the beginning of this work, the \gls{dms} may derive their +advantage through increased cytokine cross-talk. While this work found that +blocking \il{15} did not lead to differences in outcome, other cytokines could +be explored in a similar vein. + +An efficient test of this hypothesis would be to simply incubate T cells grown +with either bead or \glspl{dms} with a cocktail of \glspl{mab} each feeding +cycle that target the cytokines seen in \cref{fig:doe_luminex}, assuming that at +least a few of the targeted cytokines will cause a difference. The experiment +should be sized appropriately such that the second order interaction effect can +be resolved (that is, the effect of adding the cocktail conditional on the +activation method). In these terms, we hypothesize that the growth and phenotype +will be more similar between the beads and \glspl{dms} when the cocktail is +added, while the \gls{dms} will have better expansion and phenotype when the +cocktail is not added. If this experiment shows any effects, the cytokines +responsible can be resolved by testing individually (or in small pools). + +One caveat with this approach is that it assumes that the \gls{mab} cocktail +will completely quench their target cytokines between each feed cycle. This assumption +can be tested by running luminex with each cocktail addition. If a given +cytokine is undetectable, this indicates that the blocking \gls{mab} completely +quenched all target cytokine at the time of addition and in the time between +feeding cycles. + +\subsubsection{Interior cell phenotype} + +Unlike the beads, the \glspl{dms} have interior and exterior surfaces. We +demonstrated that some T cell expand on the interior of the \glspl{dms}, and is +plausible that these cells are phenotypically different than those growing on +the exterior or completely detached from the microcarriers, and that this leads +to an asymmetric cytokine cross-talk which accounts for the population-level +differences seen in comparison to the beads. + +Experimentally, the first step involves separating the \glspl{dms} from the +loosely or non-adhered T cells and digesting the \glspl{dms} wth \gls{cold} +(concentrations of \SI{10}{\ug\per\ml} will completely the \glspl{dms} within +\SIrange{30}{45}{\min}) isolate the interior T cells. Unfortunately, only +\SIrange{10}{20}{\percent} of all cells will be on the interior, so the interior +group may only have cells on the order of \si{1e3} to \si{1e4} for analysis. A +good first pass experiment would be to analyze both populations with a T cell +differentiation/activation state flow panel first (since flow cytometry is +relatively cheap and doesn't require a large number of cells) to simply +establish if the two groups are different phenotypes or are in a different state +of activation. From there, more in-depth analysis using \gls{cytof} or another +high-dimensionality method may be used to evaluate differential cytokine +expression. + +\subsubsection{Antibody Surface Density} + +While our \gls{doe} experiments showed a relationship between activating +\gls{mab} density and number of cells, we don't know how the \gls{mab} surface +density of the \gls{dms} compares to that of the beads. In all likelihood, the +\gls{mab} density on the \gls{dms} surface is lower (given the number of total +binding sites on \gls{stp} and the number of \glspl{mab} that actually bind) +which may lead to differences in performance\cite{Lozza2008}. + +% TODO make sure this actually is "below" +Before attempting this experiment, it will be vital to improve the \gls{dms} +manufacturing process such that \gls{mab} binding is predictable and +reproducible (see below). Once this is established, we can then determine the +amount of \glspl{mab} that bind to the beads, which could be performed much like +the \gls{mab} binding step is quantified in the \gls{dms} process (eg with +ELISA, \cref{fig:dms_flowchart}). Knowing this, we can vary the +\gls{mab} surface density for both the bead and the \glspl{dms} using a dummy +\gls{mab} as done previously with the \gls{doe} experiments in \cref{aim2a}. +Using varying surface densities that are matched per-area between the beads and +\glspl{dms} we can then activate T cells and assess their growth/phenotype as a +function of surface density and the presentation method. + +\subsubsection{Surface Stiffness} + +The beads and \gls{dms} are composed of different materials: iron/polymer in the +former case and cross-linked gelatin in the latter. These materials likely have +different stiffnesses, and stiffness could play a role in T cell +activation\cite{Lambert2017}. + +This hypotheses will be difficult to test directly, so it is advised to +eliminate other hypothesis before proceeding here. Direct testing could be +performed using a force probe to determine the Young's modulus of each +material\cite{Ju2017}. Since the microcarriers are porous and the cells will be +interacting with the bulk material itself, the void fraction and pore size will +need to be taken into account to find the bulk material properties of the +cross-linked gelatin\cite{Wang1984}. \subsection{Additional Ligands and Signals on the DMSs}