Profiling Cytosolic Drug Delivery in Mammalian Cells: A Generalizable Assay for Intracellular Accumulation

Profiling Cytosolic Drug Delivery in Mammalian Cells: A Generalizable Assay for Intracellular Accumulation | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Profiling Cytosolic Drug Delivery in Mammalian Cells: A Generalizable Assay for Intracellular Accumulation Sobika Bhandari , George M. Ongwae , Rachita Dash , Zichen Liu , Mahendra D. Chordia , Yuchen He , View ORCID Profile Marcos M. Pires doi: https://doi.org/10.1101/2025.06.03.656700 Sobika Bhandari 1 Department of Chemistry , Charlottesville, VA, United States 22904 Find this author on Google Scholar Find this author on PubMed Search for this author on this site George M. Ongwae 1 Department of Chemistry , Charlottesville, VA, United States 22904 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Rachita Dash 1 Department of Chemistry , Charlottesville, VA, United States 22904 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Zichen Liu 1 Department of Chemistry , Charlottesville, VA, United States 22904 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Mahendra D. Chordia 1 Department of Chemistry , Charlottesville, VA, United States 22904 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Yuchen He 1 Department of Chemistry , Charlottesville, VA, United States 22904 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Marcos M. Pires 1 Department of Chemistry , Charlottesville, VA, United States 22904 2 Department of Microbiology, Immunology, and Cancer University of Virginia , Charlottesville, VA, United States 22904 Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Marcos M. Pires For correspondence: mpires{at}virginia.edu Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract The ability of biologically active molecules to access intracellular targets remains a critical barrier in drug development. While assays for measuring cellular uptake exist, they often fail to distinguish between membrane-associated or endosomal trapped compounds and those that successfully reach the cytosol. Here, we present the Chloroalkane HaloTag Azide-based Membrane Penetration (CHAMP) Assay, a novel high-throughput method that employs a minimally disruptive azide tag to report the cytosolic accumulation of diverse molecules in mammalian cells. The CHAMP assay utilizes HaloTag-expressing cells and strain-promoted azide-alkyne cycloaddition (SPAAC) chemistry to quantify the presence of azide-tagged test compounds in the cytosol. We demonstrate the versatility of this approach by evaluating the accumulation profiles of small molecules, peptides, and proteins, revealing how structural variations and stereochemical differences influence cytosolic penetration. Our findings with cell-penetrating peptides confirm established structure-activity relationships, with longer polyarginine sequences showing enhanced accumulation. Additionally, we observed that C -terminal amidation and D-amino acid substitutions significantly impact cellular penetration. When applied to supercharged proteins and antibiotics, CHAMP successfully discriminates between compounds with varying accumulation capabilities. This method provides a robust platform for screening cytosolic accumulation while minimizing the confounding effects of large tags on molecular permeability, potentially accelerating the development of therapeutics targeting intracellular pathways. Introduction Small molecules, peptides, and proteins form the cornerstone of modern drug discovery, each offering distinct advantages in therapeutic applications. While small molecules constitute approximately 90% of pharmaceutical medications, proteins and peptides have emerged as promising alternatives due to their exceptional target specificity and favorable toxicity profiles. 1 Recent advances in peptide synthesis have significantly enhanced their stability and bioavailability, expanding their therapeutic potential. 2 , 3 , 4 However, a critical determinant of the therapeutic efficacy of any molecule is its ability to reach its intended target. For intracellular targets, the cell membrane represents a formidable barrier that molecules must overcome. 5 , 6 , 7 Developing effective therapies against intracellular targets presents significant challenges, particularly in quantifying molecular distribution within cells. 8 Lipinski’s “rule of five” (Ro5) has traditionally guided predictions about passive diffusion into cells 8 , yet small polar molecules and larger biomolecules (peptides, proteins, and nucleic acids) typically cannot readily traverse cell membranes directly. 9 Instead, these molecules primarily enter cells through endocytosis, often becoming trapped in endosomes rather than reaching their cytosolic targets. 10 The poorly understood process of endosomal escape further complicates therapeutic development, as conventional cell penetration assays struggle to differentiate between cellular uptake and cytosolic delivery. This highlights the urgent need for methods that can accurately measure cytosolic accessibility of potential therapeutics. 10 Current approaches to assess membrane permeability include direct quantification via LC-MS/MS or UV spectrophotometry, 11 , 12 as well as standardized permeability assays such as PAMPA and Caco-2. 13 The PAMPA technique evaluates compound permeability through an artificial membrane separating donor and acceptor compartments 14 , while the Caco-2 assay employs human colon adenocarcinoma cell monolayers to measure epithelial permeability. 15 , 16 Despite their utility, these methods have significant limitations: LC-MS/MS 17 offers excellent sensitivity but remains low-throughput 18 and cannot distinguish between membrane-bound compounds and those in the cytosol 19 , while UV spectrophotometry lacks the sensitivity required for diverse molecular screening. 20 Fluorescent tagging represents an alternative strategy for visualizing molecular localization within cells. 21 However, these tags often substantially alter the physicochemical properties of the parent molecules, potentially modifying their biological activity, cellular localization, and dynamics. 22 , 23 To address this limitation, the Kritzer laboratory developed the Chloroalkane Penetration Assay (CAPA), which utilizes a relatively smaller chloroalkane tag. 24 CAPA employs the genetically encoded HaloTag protein – a modified bacterial haloalkane dehalogenase that freely diffuses in the cytoplasm. 25 , 26 The assay involves treating HaloTag-expressing cells with chloroalkane-tagged test molecules, followed by a fluorophore-linked chloroalkane that undergoes a selective, rapid, and essentially irreversible reaction. 25 This approach generates reliable, standardized data with a direct correlation between fluorescence intensity and cytosolic accumulation, while its compatibility with flow cytometry enables high-throughput quantitative analysis. 19 Despite widespread adoption of CAPA for measuring molecular accumulation in mammalian systems, 27 , 28 , 29 a significant limitation persists: the long 15-atom chloroalkane chain tag may alter the permeability profiles and physicochemical properties of target molecules. To overcome this constraint, we have developed an improved approach that replaces the chloroalkane tag with a substantially smaller azide moiety, 30 minimizing its influence on molecular permeability 30 ( Fig. 1a ). Our strategy demonstrates that proteins, peptides, and small compounds can be modified with an azide tag to effectively determine their cytosolic localization. Furthermore, we reveal how structural and stereochemical variations influence cytosolic accumulation in mammalian cells. Combined, we present a high-throughput, efficient method for accurately determining the cytosolic accessibility of molecules across wide ranges of chemical profiles (small molecules, peptides, and proteins). Download figure Open in new tab Figure 1. (a) Structural size comparision between two functional tags: Chloroalkane (HaloTag) and azide. (b) Representation of installation of DBCOcl into HaloTag. (c) Arrival of compounds into cytosol reacts with strain alkyne handle via SPAAC reaction demonstrating cytosolic localization. (d) Schematic representation of CHAMP in mammalian cells. First cells expressing HaloTag in cytosol are treated with chloroalkane modified strained alkyne followed by treatment with azide tagged molecule "pulse step". Molecules with high level of cytosolic arrivals leave with lower number of DBCO active sites in exposure to fluorescent azide "chase step". Molecules with high level of accumulation showed lower level of cellular fluorescence. RESULTS Leveraging the subcellular localization of HaloTag in HeLa cells, we envisioned using the site-specific nature of this biochemical reaction to install a strained alkyne at defined cytosolic landmarks ( Fig. 1b ). For this step, cells are treated with the strained alkyne dibenzocyclooctyne (DBCO) linked to chloroalkane (DBCOcl). Therapeutics bearing azide groups that reach the cytosol could then be covalently captured by the HaloTags through a strain-promoted azide–alkyne cycloaddition (SPAAC, Fig. 1c ). 31 , 32 Our laboratory previously demonstrated that we can utilize this combination of DBCO and azide to evaluate the arrival of molecules to the surface and to the periplasmic space of bacteria 33 , 34 . Combined, these components result in the Chloroalkane HaloTag Azide-based Membrane Penetration (CHAMP) Assay ( Fig. 1d ) 35 . In this workflow, cytosolic accumulation of test molecules is evaluated using a pulse-chase format with azide-tagged fluorophores. After treatment, cells are analyzed by flow cytometry, and fluorescence intensity serves as a readout of cytosolic accumulation. Importantly, the fluorescence signal is inversely proportional to the permeability of the test molecule: highly permeable compounds react with and occupy most DBCO sites, resulting in low fluorescence, while poorly permeable compounds leave more DBCO landmarks available for reaction with the fluorophore, leading to higher fluorescence. This inverse relationship enables a quantitative assessment of the ability of a molecule to access the cytosol. Benchmarking Parameters – CHAMP Assay Development The presence of HaloTag in HeLa cells was first verified by treating cells stably transfected with a chloroalkane-tagged tetramethylrhodamine fluorophore (TMRcl), which covalently tags HaloTag. Wild type (WT) HeLa cells expressing only the green fluorescent protein (GFP) fusion served as negative controls ( Fig. 2a ). Flow cytometry analysis showed that there was a significant increase in cellular fluorescence in cells expressing HaloTag upon the treatment with TMRcl ( Fig. 2b ). Confocal microscopy confirmed the localization of the HaloTag expression, which is fused to GFP, and it showed that there was considerable overlap between the GFP fluorescence and the signal from the chloroalkane-linked fluorophore ( Fig. S1 ). These observations demonstrated effective cytoplasmic retention of the chloroalkane-tagged fluorophore specifically in cells expressing HaloTag. We further characterized HaloTag expression through SDS-PAGE analysis of TMRcl-treated cells, which revealed a distinct fluorescent band at the expected molecular weight (∼60 kDa) corresponding to the GFP-HaloTag fusion protein ( Fig. S2 ). We observe a single band that is fluorescent, which suggests that the covalent bond is almost exclusively at the site of HaloTag. Together, these results validated our cellular system for detecting chloroalkane-modified molecules in mammalian cells. Download figure Open in new tab Figure 2. (a) Schematic representation of the expression of HaloTag in HT HeLa cells. WT HeLa cells are used as a vehicle. (b) Flow cytometry data showing HaloTag expression. Cells were treated with 50 μM TMRcl and included no TMRcl control. WT HeLa cells were used as a negative control. Data are represented as mean ± SD (n= 3). (c) Chemical structures of azide-tagged fluorophores. (d) HT HeLa cells treated with six different azido-tagged fluorophores (TMRaz, COMaz, R110az, Flaz, Cy5az, and Cy3az). Cells were first treated with DBCOcl, washed and then treated with the 50 μM azido-tagged dyes. WT HeLa cells were used as a negative control. Data are represented as mean ± SD (n= 3). (e) SDS-PAGE analysis of cells treated with TMRcl, including a no-TMRcl control. WT HeLa cells are used as a negative control. (f) Fluorescent microscopy images showing “pulse-chase” experiment with cells pulsed with DBCOcl and chased with TMRaz. WT HeLa and HT HeLa cells not treated with DBCOcl were used as negative control. The scale bar represents 25 μm. Then, the goal was to establish the installation of strained alkyne (DBCOcl) landmarks within HaloTag. 36 This installation can be revealed with an in cyto SPAAC reaction with an azide-tagged fluorophore. We evaluated six commercially available azido-fluorophores (TMRaz, CoMaz, R110az, Flaz, Cy5az, and Cy3az) in both HaloTag-expressing and Wild type HeLa cells ( Fig. 2c ). Recognizing that their physicochemical properties could influence the extent of non-specific cellular binding, this feature was directly evaluated in HeLa cells. In each experiment, cells were first treated with DBCOcl to install DBCO onto HaloTag, followed by incubation with the respective azido-fluorophores. Among all candidates, TMRaz showed the highest fold increase in signal in the presence of HaloTag ( Fig. 2d ), making it our fluorophore of choice for subsequent experiments. Critically, these results suggest that unanchored DBCOcl in the cytosol does not significantly contribute to background signals. To confirm the covalent interaction between HaloTag-DBCO and TMRaz, we conducted fluorescent gel imaging on cells treated with or without DBCOcl followed by TMRaz ( Fig. 2e ). A fluorescent band appeared only when DBCOcl had reacted with HaloTag, confirming assay specificity. Confocal microscopy further validated the expected co-localization between the GFP signal from the HaloTag fusion and the clicked product of TMRaz ( Fig. 2f ). In HeLa cells expressing HaloTag, no apparent cellular fluorescence was observed in the absence of DBCOcl. However, when cells were treated with DBCOcl, a clear fluorescence signal emerged that overlapped with GFP signals. Collectively, these results indicate that the strained alkyne is primarily installed at HaloTag sites and that azide-tagged molecules react at the site of HaloTag. We next aimed to determine the optimal DBCOcl concentration for efficient HaloTag labeling. Cells were titrated with increasing concentrations of DBCOcl followed by a TMRaz chase step, which revealed that 10 μM of DBCOcl achieved apparent saturation of DBCO occupancy ( Fig. S3 ). In the absence of the DBCO anchor, fluorescence levels were near background; a finding that is consistent with minimal non-specific binding of the dye. To verify whether this concentration was necessary in the standard CAPA format, we performed a parallel DBCOcl concentration scan using chloroalkane-tagged TMR (TMRcl) in the chase step. Interestingly, a lower concentration of 4 μM DBCOcl generated a robust signal in this configuration ( Fig. S4 ). After establishing the working concentration parameters, we optimized incubation times. Cells were treated with DBCOcl for various times, and the cellular fluorescence was measured at each defined time point. Our results showed that the signal was effectively saturated by the first point of 2 minutes ( Fig. S5 ). These fast kinetics likely reflect a high level of accumulation efficiency, and the fast kinetics observed for HaloTag. Next, the incubation time and concentration for TMRaz was analyzed and our results showed that 50μM ( Fig. S6 ) of TMRaz labeling was required to complete the reaction within 15 minutes of then incubation ( Fig. S7 ). These optimized parameters established the working conditions for the CHAMP assay with maximum sensitivity and reproducibility. Screening of Azide-Modified Small Molecule Compounds Having established the parameters for CHAMP, we next evaluated the accumulation profiles of a large untargeted library of azide-modified compounds in the mammalian cytosol. To accomplish this, we purchased a diverse library of azide fragments containing molecules in which the azide group resides in a wide range of electronic (aliphatic/aromatic) and steric (primary/secondary/tertiary) environments that can potentially modulate reactivity with alkynes. To account for this feature, we built a parallel platform whereby the strained alkyne landmark was covalently attached to a flow cytometry-compatible polystyrene bead ( Fig. 3a ). The landmarks on the beads were then subjected to pulse-chase steps that mirror the cell treatments (same dye, same concentration, and same fluorophore). Therefore, relative changes in fluorescence signals (bead versus cells) should effectively isolate the contribution of the membrane bilayer in controlling the accessibility of the test compound to the strained alkyne ( Fig. 3b ). We measured in parallel both the bead fluorescence and cellular fluorescence of 384 compounds that varied in molecular weight, charge, polarity, hydrophobicity, rigidity, and number of hydrogen bond donors and acceptors ( Fig. 3c ). This approach highlights the ability to adapt mammalian CHAMP to a multiwell plate format that can readily be employed in high-throughput workflows. While the generally small size of these fragment-like molecules prevented a deeper analysis that could broadly contribute to defining the accumulation determinants (e.g., in combination with machine learning algorithms), patterns of accumulation could be generally correlated with physicochemical parameters such as ClogP and TPSA ( Fig. 3d ). Nonetheless, this level of throughput can be readily paired with a library that has the chemical space to more thoroughly probe how small molecule structure drives accumulation to the cytosol. Download figure Open in new tab Figure 3. (a) Assessing probe permeability in beads (no barrier) versus live cells (membrane bilayer barrier). (b) Interpretation of membrane bilayer impact on DBCO labeling observed for both permeable and non-permeable compounds. (c) Comparison of apparent accumulation between bead and cell DBCO labeling of the 384-azido compound library. Accumulation relative to vehicle control is measured using the CHAMP assay and reactivity relative to vehicle control is measured using the DBCO-tagged polystyrene beads assay. (d) Effect of six different physiocochemical parameters on accumulation profiles of 384 azido library. For all CHAMP assays, HT HeLa cells were treated with DBCOcl, then incubated with the azide tagged molecules for an hour. Data are represented as mean +/- SD (n = 3). Next, we set out to probe how targeted structural edits, with a focus on charged states, can be systematically evaluated using CHAMP. The charged state of molecules can broadly impact desolvation profiles in the case of passive diffusion across the membrane bilayer. When charged species are important to impart biological activity, prodrug strategies are commonly employed to temporarily mask the charges, which can lead to enhanced drug delivery. 37 Given that carboxylic acids are amongst the most abundant functional groups found in pharmaceuticals, we benchmarked CHAMP by testing how the presence of an unprotected carboxylic acid affects the intracellular accumulation of small molecules in mammalian cells. To this end, we selected scaffold 1 , comparing variants with either an amidated ( 1p ) or free carboxylic acid ( 1n ) at the C -terminus. As anticipated, the amidated derivative 1p exhibited greater accumulation than its free acid counterpart 1n ( Fig. 4a ). We then extended our analysis to a slightly larger scaffold ( 2 ) in which the amino group was positioned further from the C -terminus, thus avoiding potential internal hydrogen bonding configurations. A similar trend was observed: amidated 2p accumulated more efficiently than 2n , although both compounds showed reduced accumulation relative to scaffold 1 , likely due to increased molecular size ( Fig. 4b ). Finally, we investigated scaffold 3 , which lacks an amino group, to assess whether the overall molecular charge – net neutral or negative in this case, as opposed to net positive or neutral in scaffolds 1 and 2 – influences cellular accumulation. As before, 3p outperformed 3n in accumulation ( Fig. 4b ). Download figure Open in new tab Figure 4 (a) Chemical structures of the 1-3 series. (b) Apparent accumulation of 50 μM of 1p, 1n, 2p, 2n, 3p, and 3n. (c) Chemical structure of 4-5 series. (d) Apparent accumulation of 50 μM of 4a-4d. (e) Apparent accumulation of 50 μM of 5a-5d. (f) Chemical structure of azide modified antibiotics. (g) Comparative accumulation of 50 μM of azide modified antibiotics. Apparent accumulation was measured using CHAMP assay. Data are represented as mean ± SD (n= 3) The methylation of amine groups can modulate the overall charge and hydrophobicity of a molecule, thereby influencing its cellular accumulation. The Hergenrother group has previously demonstrated that primary amines are privileged functional groups for promoting accumulation in E. coli . 38 To empirically assess how the degree of amine methylation affects accumulation in mammalian cells, we synthesized and evaluated scaffolds 4 and 5 , each differing in amine methylation patterns. The 4 series was based on a scaffold similar to 3 , with compounds 4b - 4e containing progressively increasing methylation on the amine, and 4a bearing a terminal hydrocarbon in place of an amino group ( Fig. 4c ). Upon evaluation, compound 4a showed significantly lower accumulation compared to the un-, mono-, and di-methylated analogs 4b - 4d , which exhibited comparable accumulation levels ( Fig. 4d ). In contrast, the trimethylated amine 4e displayed the poorest accumulation in the series. To validate these observations in a complementary assay, we synthesized series 5 , which is structurally analogous to series 4 but functionalized with a small fluorophore ( Fig. 4c ). This modification enabled direct measurement of accumulation. Consistent with the trends observed in series 4 , compound 5a accumulated less than 5b - 5d , which showed comparable accumulation levels, while the trimethylated analog 5e again exhibited the lowest accumulation ( Fig. 4e ). Several intracellular bacteria, including Legionella pneumophila , Salmonella enterica , and members of the Mycobacterium genus, reside and replicate in the cytosol of host cells, causing various bacterial infections. 39 We previously showed that antibiotics have a range of accumulation to the surface of bacteria once S. aureus is housed inside phagosomes but that analysis was devoid of cytosolic description. This is important because a subset of bacterial pathogens also reside in the cytosol. Antibiotic treatment of these intracellular bacteria often shows limited effectiveness. However, it remains unclear whether the failure of these well-known antibiotics is due to their inability to permeate the cell membrane and reach their targets or because bacteria become resistant to the antibiotics in this environment. 40 To evaluate the accumulation profiles of different antibiotics, we modified a panel of antibiotics with azide groups to make them compatible with the CHAMP workflow ( Fig. 4f ). These antibiotics target various cellular proteins, many of which are located in the cytosol. 41 For these antibiotics to be effective, they must cross the membrane barrier and reach their targets. Among the antibiotics with similar reactivity, our results revealed that other than three antibiotics – purAZ1, zolAZ3, and sulAZ1 – showed significantly higher fluorescence signals, indicating more cytosolic accumulation ( Fig. 4g ). Accumulation Studies of Super-charged Peptides We next utilized the CHAMP workflow to assess the cytosolic accumulation of cell-penetrating peptides (CPPs). Since the development of the first CPPs, Tat and penetratin, the field has rapidly advanced and continue to utilize the unique properties of CPPs to promote the delivery of cargo to the inside of cells. 42 , 43 , 44 CPPs are generally cationic or amphipathic peptides composed of relatively few residues (fewer than 30 amino acids) that efficiently transport a range of macromolecules across cell membranes when conjugated to them. 45 , 46 To evaluate the ability of CHAMP to report CPP accumulation in the cytosol of mammalian cells, we synthesized a series of azide-modified polyarginine peptides (R5az, R7az, R9az, and R11az, Fig. S8 ). Cells treated with these peptides at varying time points were tested to empirically determine the optimal experimental time course. Our findings revealed that a 24-hour peptide incubation was required to achieve full apparent accumulation ( Fig. 5a ). We then performed a concentration scan of the peptides using this optimized time condition ( Fig. 5b ). The results demonstrated a positive correlation between the number of arginine residues (ranging from 5 to 11) and cellular accumulation, consistent with previous reports. 47 , 48 , 49 Mechanistically, guanidine groups are believed to play a critical role in cell penetration by electrostatically interacting with sulfate, phosphate, and carboxylate moieties on the cell surface. 50 Our results indicated that R5az exhibited the lowest accumulation among the tested polyarginines while both R9az and R11az showed the highest apparent accumulation. To further test the role of the membrane in reducing apparent accumulation, cell were treated with digitonin, a non-ionic detergent that permeabilizes membranes by complexing with membrane cholesterol, 51 in the presence of polyarginine peptides. Before testing the peptides with digitonin, we first evaluated an azide tagged dye with inherently low cellular permeability to confirm that membrane disruption facilitates intracellular entry. Based on prior reports, we selected sCy5az, a sulfonated cyanine molecule with an azide group, which is expected to exhibit minimal permeability due to its sulfonate groups. 52 Compared to cell treatment of with dye alone, pre-incubation with digitonin significantly increased fluorescence signal ( Fig. S9 ). These findings highlight that the plasma membrane acts as a barrier to molecular entry, and its permeabilization enhances intracellular access. Further, they suggest that CHAMP can be used to monitor the integrity of the plasma membrane in the presence of potentially membrane-disrupting agents when paired with highly anionic dyes that are azide-tagged. Building on this result, we tested digitonin with polyarginine peptides, specifically R5az (low apparent accumulation) and R11az (high apparent accumulation). Our data showed that in the presence of 40 μg/mL digitonin, R5az displayed a higher apparent accumulation profile to the cytoplasm of mammalian cells ( Fig. 5c ). This indicates that digitonin successfully permeabilized the membrane, allowing the peptide to reach its target in the cytosol. Download figure Open in new tab Figure 5 (a) Optimization of time of incubation of polyarginine peptides. Four different time points were tested: 2,4,6, and 24 h. Cells treated with DBCOcl were pulsed with 50 μM of peptides and chased with 50 μM TMRaz. Data are represented as mean ± SD (n= 3). (b) Concentration scan of polyarginine peptides at six different concentrations: 2.5, 5, 10, 15, 25, and 50 μM. DBCOcl-treated cells were pulsed with 50 μM of peptides and chased with TMRaz. Data are represented as mean ± SD (n= 3). (c) CHAMP assay with and without 40ug/mL of digitonin. DBCOcl-treated cells were pulsed with two peptides with different accumulation profiles in presence and absence of digitonin followed by a chased step with TMRaz. Data are represented as mean ± SD (n= 3). (d) Comparison of effect of stereochemistry on accumulation of polyarginine peptides using CHAMP assay. Cells treated with DBCOcl were pulsed with 50 μM of compounds for 24 h and chased with 50 μM of TMRaz. Higher fold change is indicative of higher relative accumulation. Data are represented as mean ± SD (n= 3). Data are represented as mean ± SD (n= 3). (e) Chemical structure of L and D Fmoc-Lysaz. (f) Comparison of effect of stereochemistry on accumulation of dipeptides using CHAMP assay. Cells treated with DBCOcl were pulsed with 50 μM of compounds for 1 h and chased with 50 μM of TMRaz. Higher fold change is indicative of higher relative accumulation. Data are represented as mean ± SD (n= 3). (g) Apparent accumulation of 36GFPaz using CHAMP assay. Cells were treated with DBCOcl followed by treatment with supercharged protein and chased with dye (TMRaz). Unlabeled 36GFP was used as control. Data are represented as mean ± SD (n= 3). Additionally, we investigated the impact of stereochemistry on cytosolic accumulation in mammalian cells. Some models of permeation focus on the octanol–water partition coefficient 53 , which can provide useful insights into the molecular state after complete solvation by the bulk solvent. Yet, these models fail to capture the potential interaction at the water-lipid interface that can operate with stereochemical elements of phospholipids. This is important because, in theory, this interaction prior to permeation could impact the residency time and promote entry into the lipid bilayer. To this end, diastereoselective permeation was previously demonstrated in ribose using phospholipid bilayers but not enantiomers of xylose. 54 We reasoned that we could leverage CHAMP to empirically test how the stereochemistry of molecules can alter cytosolic accumulation of molecules in live cells. Given that polyarginines are generally purported to interact with the headgroups of lipids in mammalian bilayers, we explored the role of stereochemistry in polyarginine accumulation by synthesizing all D-version of R9, r9. Our data showed that R9 accumulated more efficiently to the cytosol of mammalian cells in both minimal media ( Fig. 5d ) and complete media ( Fig. S9 ). The use of complete media was to reduce the potential for protease-based degradation of the peptide during the incubation period. These results agree with previous results but additionally showed that the prior results also reflect the accumulation into the cytosol (as opposed to whole cell). 55 , 56 Next, we took a complementary approach that focused on a non-peptidic small molecule. The goal was to evaluate how stereo configuration could potentially alter accumulation in live cells. For this series, we used Fmoc-L-Lysaz acid and Fmoc-D-Lysaz acid for their apparent accumulation to the cytosol of mammalian cells ( Fig. 5e ). Interestingly, we found that D-enantiomer had a higher level of apparent accumulation than its L-form counterpart, which may indicate stereospecific engagement with the headgroup of a lipid in a live cell ( Fig. 5f ). More recently 57 , enantioselective accumulation of amino acids, also using click-chemistry to measure accumulation, was demonstrated in chiral lipid bilayers (not in a live cell), a finding that could be matched upon inversion of the stereocenters and lost upon disruption to the chirality of the lipid headgroups. Similarly, the enantiomeric counterpart of the antibiotic polymyxin was shown to be stereoselective in its engagement with the headgroup of lipid A on the surface of bacteria. 58 Together, our results highlight how CHAMP can be leveraged to interrogate features related to the three-dimensionality of a compound and its impact on accumulation across membrane bilayers. There is growing recognition of the importance of developing protein-sized drugs, such as antibodies, nanobodies, and engineered protein scaffolds, that target intracellular pathways. 59 , 60 , 61 Traditionally, these larger biomolecules were confined to extracellular targets due to their limited ability to cross cellular membranes. We then postulated that our technique could be applied to analyze the accumulation profiles of larger macromolecules, such as supercharged proteins. Superpositively charged proteins, like +36 GFP, have been shown in multiple studies to accumulate at significantly higher levels than cationic peptides or mildly cationic designed proteins. 62 , 63 These proteins are known for their remarkable resistance to denaturants and their robust folding properties. 64 We anticipated that their positive charges would facilitate electrostatic interactions with the cell surface, thereby promoting internalization. 63 Critically, the installation of azides can be readily performed via metabolic techniques such as the incorporation of non-canonical amino acids (ncAAs) by genetic dose expansion 65 or by Biorthogonal Non-Canonical Amino Acid Tagging (BONCAT). 66 Alternatively, azide groups can be installed using electrophilic reagents such an N -hydroxysuccinimide (NHS). To probe for cytosolic arrival of GFP variants, we expressed both wild-type and supercharged GFP (+36) and tagged these proteins with an azido tag using an azido-NHS ester. Gel analysis showed that both proteins and, upon reacting with TAMRA-tagged azide, fluorescence gel analysis showed that they were approximately the same level of labeling. Similar to the whole cell association results using confocal microscopy, we observed that positively supercharging the protein can promote their cytosolic arrival relative to wildtype GFP ( Fig. 5g ) . Notably, the unlabeled +36GFP without the azide tag showed no accumulation, indicating that the azide tag was essential for change in cellular fluorescence. Thus, our findings demonstrate that supercharged proteins can accumulate in the cytoplasm of mammalian cells, further validating the application of our technique for studying the intracellular delivery of macromolecules. Effect of Macrocyclization and N -alkylation on Peptide Accumulation Macrocyclization and N -alkylation are two commonly employed strategies utilized to enhance membrane permeability. 67 , 68 , 69 , 70 , 71 N -alkylation reduces the number of solvent-accessible hydrogen bond donors, thereby lowering the desolvation penalty associated with passive diffusion. 72 Similarly, macrocyclization can promote intramolecular hydrogen bonding, which further mitigates desolvation costs by shielding polar groups from solvent. 73 , 74 , 75 To systematically evaluate the impact of these modifications on peptide accumulation in mammalian cells, we tested a systematically varied library of azide-tagged macrocyclic and N -alkylated peptides. First, we evaluated a sub-library of peptides of increasing sizes Cyc0 – 3 , alongside their linear analogs Lin0 – 3 to gauge the influence of molecule size on accumulation ( Fig. 6a ). 76 , 77 In all four pairs, the cyclic peptides generally exhibited greater intracellular accumulation compared to their linear counterparts. Additionally, both series displayed a size-dependent decrease in accumulation, with larger peptides accumulating to a lesser extent ( Fig. 6b ). Download figure Open in new tab Figure 6. (a) Chemical structures of the linear vs macrocyclic sub-library members containing macrocyclic peptides of increasing sizes (Cyc0-3) and linear counterparts (Lin0-3). (b) Apparent accumulation of linear vs macrocyclic sub-library using CHAMP assay. Cells treated with DBCOcl were pulsed with 50 μM of compounds for 24 h and chased with 50 μM of TMRaz. (c) Chemical structure of the ring size (lariat) sub-library members containing macrocyclic peptides of increasing ring sizes (Lar1-5) and their linear counterpart (Lar0). (d) Apparent accumulation of the ring size sub-library. Cells treated with DBCOcl were pulsed with 50 μM of compounds for 24 h and chased with 50 μM of TMRaz. (e) Chemical structures of the cyclization chemistry sub-library members containing a disulfide bonded macrocyclic peptide (Dit1), a bis-electrophilic linker based macrocyclic peptide (Dit2) and their linear counterpart (Dit0). (f) Apparent accumulation of the cyclization chemistry sub-library. Cells treated with DBCOcl were pulsed with 50 μM of compounds for 24 h and chased with 50 μM of TMRaz. Data are represented as mean ± SD (n= 3). Peptides that are characterized by a looped or "lasso" structure are known as lariats and have recently been explored as drug scaffolds. 78 , 79 We evaluated a series of lariat peptides with decreasing ring sizes Lar1 – 5 along with a linear control Lar0 ( Fig. 6c ). Consistent with previous observations, the cyclic peptides generally outperformed the linear analog. Although no clear trend emerged across the cyclic series, the peptide with the smallest ring – Lar5 , exhibited the highest accumulation ( Fig. 6d ). This result was unexpected, as smaller rings typically expose more surface area to solvent, potentially diminishing the accumulation advantages conferred by cyclization. To evaluate whether an alternative cyclization strategy could also enhance accumulation, we assessed the Dit0 – 2 series ( Fig. 6e ). Dit1 , a disulfide-containing peptide, was generated by oxidizing a dithiol scaffold. Using the same linear precursor, we synthesized Dit2 via cyclization with a bis-electrophilic linker, yielding two thioether bonds. Dit0 , served as the linear control. As observed previously, both cyclic peptides accumulated more effectively than the linear analog ( Fig. 6f ). Notably, Dit1 outperformed Dit2 , underscoring the impact of cyclization chemistry on accumulation. This difference may arise from variations in conformation, structural rigidity, or hydrophobicity—factors that can influence membrane permeability. 80 Within the N -alkylated library, we first examined how the degree of N -methylation affects peptide accumulation by evaluating peptides N met1 – 5 in comparison to their unmethylated counterpart, Nmet0 ( Fig. 7a ). A modest increase in accumulation was observed with the addition of up to two N -methyl groups ( Fig. 7b ). Beyond this point, no significant differences were noted among peptides containing two, three, or four N -methyl groups. However, a slight decrease in accumulation was observed when five N -methyl groups were introduced. Upon evaluating peptides bearing a single N -methylation at different backbone amide positions ( Nmet6 - Nmet9 and Nmet1 ) ( Fig. 7c ), we observed clear positional effects on cytosolic accumulation, with Nmet9 showing the highest level of uptake ( Fig. 7d ). Importantly, positional and degree effects of N -methylation have previously been observed 81 , 82 , 83 , 84 , 85 , 86 underscoring the importance of empirical evaluation when optimizing N -methylation patterns for intracellular delivery. Download figure Open in new tab Figure 7. (a) Chemical structures of the N -methylation sub-library with varying degrees of backbone N -methylation (Nmet0-5). (b) Apparent accumulation of the N -methylation sub library with varying degrees of backbone N-methylation using CHAMP assay. Cells treated with DBCOcl were pulsed with 50 μM of compounds for 24 h and chased with 50 μM of TMRaz. (c) Chemical structures of the N -methylation sub-library with varying positions of backbone N -methylation (Nmet6-9 and Nmet1). (d) Apparent accumulation of the N -methylation sub-library with varying positions of backbone N -methylation. Cells treated with DBCOcl were pulsed with 50 μM of compounds for 24 h and chased with 50 μM of TMRaz. Data are represented as mean ± SD (n= 3). Peptoids, which are N -substituted glycine oligomers bearing side chains on the backbone nitrogen rather than the α-carbon, have been investigated as scaffolds for targeting drug-resistant bacterial pathogens. 87 , 88 , 89 , 90 In this context, we tested a series of peptoids analogous to our N -methylated peptide library ( Fig. S11 ). As observed previously, accumulation increased slightly with the addition of up to two methylation marks, with no further improvement beyond that point. Notably, in assessing positional effects, Nalk9 analogous to the top-performing positional series N -methylated peptide, Nmet9 emerged as the most privileged scaffold in the series ( Fig. S12) . Overall, our analysis revealed that macrocyclization generally enhances accumulation into the mammalian cytoplasm, whereas the effects of N -methylation are more context- and position-dependent, varying across different substitution patterns. Conclusions In conclusion, the CHAMP assay builds upon the foundational CAPA methodology to evaluate the intracellular accumulation of azide-tagged molecules, offering a minimally disruptive alternative to chloroalkane tags, which could otherwise affect uptake and intracellular distribution. CHAMP reliably quantifies the cytosolic penetration of a wide range of compounds, including small molecules, peptides, and proteins. The system effectively identifies variations in accumulation profiles based on structural and stereochemical differences, supporting comparative studies of azide-modified compounds in mammalian cells. Furthermore, we envision CHAMP as a tool capable of reporting accumulation differences across various subcellular organelles using signal peptides. This would enable the measurement of molecular accumulation in the nucleus, outer mitochondrial membrane, endoplasmic reticulum, Golgi apparatus, peroxisomes, or lysosomes. Such capabilities could provide valuable insights into the role of mono- or bilayer subcellular membranes in molecular permeation, ultimately advancing the development of effective intracellular therapies by overcoming the challenges of measuring cytoplasmic accumulation with small tags. ACKNOWLEDGEMENT This study was supported by the NIH grant 1R01AI178975-01 (M.M.P., W.I, and S.S.), R35GM124893 (M.M.P.), R01AI179080-01 (M.M.P., W.I, and S.S.) and the NSF grant MCB-2111728 (W.I.). Funder Information Declared National Institute of Health , R35GM124893 References (1). ↵ Fosgerau , K. ; Hoffmann , T . Peptide Therapeutics: Current Status and Future Directions . Drug Discovery Today 2015 , 20 ( 1 ), 122 – 128 . doi: 10.1016/j.drudis.2014.10.003 . OpenUrl CrossRef PubMed (2). ↵ Pei , J. ; Gao , X. ; Pan , D. ; Hua , Y. ; He , J. ; Liu , Z. ; Dang , Y . Advances in the Stability Challenges of Bioactive Peptides and Improvement Strategies . Current Research in Food Science 2022 , 5 , 2162 – 2170 . doi: 10.1016/j.crfs.2022.10.031 . OpenUrl CrossRef PubMed (3). ↵ Lau , J. L. ; Dunn , M. K . Therapeutic Peptides: Historical Perspectives, Current Development Trends, and Future Directions . 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A. ; Banville , S. ; Ng , S. ; Wang , L. ; Rosenberg , S. ; Marlowe , C. K . Peptoids: A Modular Approach to Drug Discovery . Proceedings of the National Academy of Sciences 1992 , 89 ( 20 ), 9367 – 9371 . doi: 10.1073/pnas.89.20.9367 . OpenUrl Abstract / FREE Full Text View the discussion thread. Back to top Previous Next Posted June 06, 2025. Download PDF Supplementary Material Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Profiling Cytosolic Drug Delivery in Mammalian Cells: A Generalizable Assay for Intracellular Accumulation Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. 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