Skip to main content
JACS Au logoLink to JACS Au
. 2024 Feb 26;4(4):1450–1457. doi: 10.1021/jacsau.4c00001

Development of a Mature B Lymphocyte Probe through Gating-Oriented Live-Cell Distinction (GOLD) and Selective Imaging of Topical Spleen

Heewon Cho , Haw-Young Kwon †,, Youngsook Kim §, Kyungwon Kim §, Eun Jig Lee §, Nam-Young Kang , Young-Tae Chang †,‡,*
PMCID: PMC11040558  PMID: 38665660

Abstract

graphic file with name au4c00001_0005.jpg

B lymphocytes play a pivotal role in the adaptive immune system by facilitating antibody production. Young B cell progenitors originate in the bone marrow and migrate to the spleen for antigen-dependent maturation, leading to the development of diverse B cell subtypes. Thus, tracking B cell trajectories through cell type distinction is essential for an appropriate checkpoint assessment. Despite its significance, monitoring specific B cell subclasses in live states has been hindered by a lack of suitable molecular tools. In this study, we introduce CDoB as the first mature B cell-selective probe, enabling real-time discrimination of three classified stages in B-cell development: progenitor, transitional, and mature B cells, through a single analysis using CyTOF. The selective mechanism of CDoB, elucidated as gating-oriented live-cell distinction (GOLD), targets SLC25A16, identified through systematic screening of SLC-CRISPRa and CRISPRi libraries. CDoB selectively brightens mature B cells in the mitochondrial area using SLC25A16 as the main gate, and the staining intensity correlates positively with the expression level of SLC25A16 along the B cell maturation continuum. In spleen tissues, CDoB demonstrates selective marking in mature B cell areas in live tissue status, representing the first performance achieved by a small-molecule fluorescent probe.

Keywords: fluorescent carbohydrate library, high-throughput phenotypic screening, gating-oriented live-cell distinction, solute carrier, mature B cell specific probe, spleen topical imaging

Introduction

The main players in the adaptive immune system are T and B lymphocytes. While T lymphocytes participate in cytotoxic responses, B cells are responsible for antibody production. Given the similarity in shape and size between T and B lymphocytes, it has long been believed that discriminating between the two cell types is practically impossible without the aid of fluorescently labeled antibodies targeting cell surface biomarkers such as cluster of differentiation (CD) markers. However, our research has demonstrated that the development of small molecule fluorescent probes for cell-selective distinction is feasible through the diversity-oriented fluorescence library (DOFL). With these fluorescent probes, we can not only monitor dynamic cellular states but also uncover intrinsic cellular activities without disturbance.1

We have developed two B cell selective probes CDgB(2) and CDyB,3 which exhibit specificity over T cells. While we achieved general selectivity for B lymphocytes, we recognized the need to differentiate specific B cell subsets. This consideration arises from the potential for particular B cell subclasses to serve as useful indicators for evaluating histopathology based on cellular compartments or formations, such as in the spleen (SP).4 Furthermore, tracking B cell trajectories is deemed crucial for proper checkpoint assessment during maturation.5 Consequently, our focus has shifted toward further discriminating B cell subsets throughout their developmental stages.

B cell precursors differentiate from hematopoietic cells in the bone marrow (BM) (Figure S1). Following the early stage of progenitor B cells (pro-B, pre-B, and immature B cells), they migrate to the SP for antigen sensing and further maturation. Immature B cells settle into transitional type 1 B (T1 B) and type 2 B cells (T2 B) successively before maturing into Follicular (FO) B cells and marginal zone (MZ) B cells.6 A portion of matured B cells may return to the BM as recirculating B cells.7 Thus, B cells can be classified into three main subgroups: progenitor (pro-B, pre-B, and immature B cells), transitional (T1 and T2 B cells), and mature (FO, MZ, recirculating B cells), depending on their maturation stages.

To elicit a more specific B cell probe, we introduced the luminescent-carbohydrate (LC) library to the SP. This approach expands the utility of carbohydrate bioprobes beyond cancer cells, which have notably increased uptake rates of carbohydrates,8 to image specific immune cell types such as macrophage subsets9 beyond cancer cells that have striking increased uptake rates of carbohydrates.

In this study, we introduce the first mature B cell-selective probe, CDoB (compound designation “orange” or “old” B cell), capable of monitoring the B cell maturation process based on its intensity. Through the utilization of both the SLC-CRISPRa and CRISPRi screening systems, we identified the specific transporter, SLC25A16, which is overexpressed in mature B lymphocytes compared with other subtypes. Furthermore, we demonstrated CDoB’s ability to selectively enhance the region of mature B lymphocytes in live SP tissues.

Results and Discussion

Discovery of a Stratified Mouse B Lymphocyte Selective Probe

To discover a specific B cell subset probe from the LC library, we established an efficient screening format10 utilizing the SP, which primarily comprises B lymphocytes (around ∼70%) along with a minor population of T cells (Figure 1A).11 Initially, the murine SP was dissociated into single cells of splenocytes, and 1 μM LC compounds were added to the cells. After 1 h, the samples were analyzed using flow cytometry (Figure S2 and Table S1). Based on the outcomes, we calculated the SI to assess the degree of separation in the splenocytes and represented the values in a heat map (Figures 1B and S3). We identified four lead compounds that further divided splenocytes into two groups, but unexpectedly, these molecules shared the same fluorophore. Although we investigated whether only the core structure possessed discriminatory capacity, it failed to distinguish the cell populations (Figure S4). Subsequently, we varied the incubation time up to 4 at 1 h intervals (Figures 1C, S5, and S6). Interestingly, the F5 index showed a significantly higher point at 4 h compared to other molecules, demonstrating three distinct cell populations. Intrigued by this unique pattern, F5 was selected for further study. It was observed that F5 exhibited preferential selectivity for B cells over T cells after 1 h (Figure 1D,E). Furthermore, the two brighter populations among the three splits were identified as B lymphocytes (Figures 1F and S7). Since F5 consists of an orange fluorophore attached to galactose at the 2-carbon position, along with comprehensive recognition of B cells (Figure 1G), it was named CDoB (compound designation orange B). These results suggest that both the fluorophore and the carbohydrate moiety contribute to its specific selectivity.

Figure 1.

Figure 1

Development of a mouse B cell selective probe. (A) Flowchart of screening with the LC library. (B) Heat map of the stain index (SI) is based on screening results. (C) Deep investigation of behaviors of lead compounds by tracking for 4 h. (D) Total splenocytes were first stained with anti-CD3 (T cell) and then CDoB for 1 h. (E) T and B cells from splenocytes were isolated using MACS (magnetic-activated cell sorting). Each cell type was stained with CDoB for 1 h and then read with flow cytometry. (F) Three splits were observed after 4 h of staining with CDoB. (G) Chemical structure of CDoB. The images were taken by a 100 objective oil lens. P, positive; N, negative; M, median fluorescent intensity at half-height; rSDn, robust standard deviation of negative at half-height. Circle (•), LC-B4; square (■), LC-D5; triangle (▲), LC-F5; diamond (◆), LC-H5.

Cell Type Identification by CDoB Intensity

We identified that CDoB has a strong potential to recognize a specific B cell subtype by distinguishing the B cell groups into two subsets. To deeply investigate CDoB selectivity, BM and SP were analyzed together, enriching diverse B cell subsets involved in B cell development.

Single cells were initially obtained from BM and SP, respectively, and then CDoB was added (Figure 2A). After 4 h, we observed distinct staining patterns in BM compared to the SP based on CDoB intensity (Figure 2B). While CDoB separated the splenocytes into three groups, CDoB++ (double positive), + (single positive), and – (negative), only CDoB++ and CDoB– groups were detected in BM. Subsequent to these findings, we sorted out each of the five groups (two from BM, three from SP). Conventional flow cytometry techniques are inadequate due to limited channels and significant emission spectra overlay.12 However, cytometry by time of flight (CyTOF) can simultaneously analyze over 90 parameters by targeting cells with a cocktail of antibodies conjugated with heavy metal isotopes. Additionally, CyTOF is effective for capturing slight variations in biomarker expression in a single analysis, as data from each sample are plotted in a two-dimensional graph concurrently. Leveraging the advantages of CyTOF, we designed antibody panels to encompass B cell subsets in both BM and SP,13 as well as T and NK cells14 (Tables S2 and S3). Subsequently, we incubated the sorted cells with metal-labeled antibodies, and the samples were analyzed by CyTOF. The five data sets were combined, generating a two-dimensional map using the t-SNE (t-distributed stochastic linear embedding) algorithm (Figure S8).

Figure 2.

Figure 2

Cell type identification with CDoB. (A) Schematic view of experimental procedures. (B) Separation patterns of BM and SP after 4 h of CDoB staining. (C) Analysis data of CyTOF after sorting out cells followed by CDoB intensity. FO B: follicular B, MZ B: marginal zone B; T1 B: transitional type 1 B. T2 B: transitional type 2 B, HSCs: hematopoietic stem cells. (D) Illustration of CDoB selectivity in BM and SP. B cell progenitors (Pro-B, Pre-B, and immature B) in BM are the dimmest along with NK and T cell. These cells immigrated to SP and transferred into transitional B cells (T1 B, T2 B) that showed middle intensity of CDoB. Both B cell progenitors and transitional B cells finally developed into mature B cells (MZ B, FO B, and recirculating B) which are the brightest community of CDoB.

The t-SNE maps clustered different phases of B cells along with T lymphocytes and NK cells based on differently expressed antibodies, delineating the lineage of SP (green) and BM (orange) with colored dots (Figure 2C). Interestingly, the results revealed that CDoB can monitor B cell developmental stages. The CDoB++ populations included mature B cells (FO B, MZ B, recirculating B), whereas CDoB+ contained transitional B cells, and CDoB– consisted of B cell progenitors (pro-B, pre-B, and immature B), T, and NK cells (Figure 2D). This performance contrasts with previously reported B cell probes, CDgB(2) and CDyB,3 which have low sensitivity to monitor overall B cell stages from BM to SP. This result underscores the efficacy of CDoB as an ideal tool for tracking B cell maturation, especially in selectively highlighting mature B lymphocytes, leading to its designation as Compound Designation for old B.

Elucidation of the Selectivity Mechanism and the Target Validation of CDoB

Considering the molecular structure and localization of CDoB, we hypothesized that CDoB may utilize a specific transporter associated with mature B cells. While transporters are broadly categorized into solute carrier (SLC) and ATP-binding cassette (ABC) transporters,15 SLCs are especially recognized as influx transporters responsible for translocating molecules across cell membranes. With over 400 members and a wide range of selective substrates, the diversity of SLCs may offer insights into CDoB’s affinity toward mature B lymphocytes. Therefore, we established a CRISPR-based SLC screening platform (Figure 3A). This system lacked endonuclease activity and controlled target gene expression by introducing effectors: VPR (activation)16 or KRAB (suppression).17 We selected approximately 380 protein-encoded SLC genes from the NCBI gene database and designed 10 single guide RNAs (sgRNAs) for each SLC gene with dCas9-VPR, generating 3800 members of the SLC-CRISPRa (activation) library initially.18 Using the SLC overexpression system, the top 3–5% of the brightest CDoB populations were repeatedly sorted and expanded until distinctly bright populations were enriched. After 7 rounds, the sorted CDoB-bright populations showed significant enrichment compared to control cells (Figure S9). Next-generation sequencing (NGS) analysis revealed four enriched target genes: SLC17A2, SLC52A2, SLCO1B3, and SLC25A16, each appearing in similar proportions (approximately 25%).

Figure 3.

Figure 3

Target identification and validation of CDoB. (A) Schematic process of SLC-CRISPRa and CRISPRi screening and the results. (B) Localization of CDoB was confirmed in murine primary B cells, and (F) correlation graph and numeric value of Pearson’s correlation coefficient (0.99). ×100 oil objective lens; scale bar: 10 μm. (C) CRISPR-sls25a16-Knockout (KO) was applied to the WEHI-231 cell line. (D) mRNA expression level of slc25a16 in both control and KO cells. (E) After CRISPR-KO, CDoB intensity was diminished in KO cells. ×40 objective lens; scale bar: 20 μm.

To further narrow down the target transporter, we conducted SLC-CRISPRi screening, which suppressed SLC expression using dCas9-KRAB. Unlike SLC-CRISPRa, we sorted out the 3–5% dimest CDoB populations and analyzed the sequences from the sorted cells (Figure S10). Interestingly, we identified the overlapping gene, SLC25A16, derived from both CRISPRa and CRISPRi screening analyses. Based on these results, we focused on SLC25A16, known as a mitochondrial carrier,19 Subsequently, we identified that CDoB localizes to mitochondria in B lymphocytes with a high correlation coefficient with Mitotracker (0.99) (Figure 3B). Combining these outcomes, we sought to validate whether CDoB utilizes SLC25A16 to localize to the mitochondrial area using the CRISPR-Knockout (KO) technique in the mouse B cell line, WEHI-231 (Figure 3C). After slc25a16 gene deletion (Figure 3D), CDoB intensity significantly decreased compared to the control (Figure 3E). Furthermore, we confirmed the expression level of slc25a16 in each of the five sorted populations from BM (CDoB++, −) and SP (CDoB++, + , −), revealing a correlation with CDoB intensity and suggesting SLC25A16 as an indicator in B cell developmental processes (Figures S11 and S12).

This performance elucidated the selective mechanism of CDoB through gating-oriented live-cell distinction (GOLD) with SLC25A16 overexpressed in mature B lymphocytes. It marks the first achievement in identifying the molecular target utilizing both SLC-CRISPRa and CRISPRi screening formats. Furthermore, SLC25A16 is considered an orthologue of Leu5p, a yeast protein, which utilizes coenzyme A as a substrate.20 However, due to the lower homology of the protein between mouse and yeast (approximately 38%), it would be difficult to assume that coenzyme A serves as a substrate for murine SLC25A16.21 As a result, to the best of our knowledge, CDoB represents the first clear substrate identified in murine SLC25A16. We believe that this finding will pave the way for in-depth functional studies of murine SLC25A16.

Visualization of Mature B Cells with CDoB in the SP Tissue

Monitoring immune cells in the SP is crucial, given that the SP is an appropriate organ for assessing histopathology based on its size and cellular compartments.4 Building on CDoB selectivity, we investigated its ability to distinguish mature B cells in the splenic tissue.

First, we confirmed cellular locations in the SP using antibodies. The interior consists of a T cell zone (blue) surrounded by mature B cells (red). Interestingly, the region of transitional B cells (green)22 was situated outside of mature B cells (Figure 4A). The clearly defined sections reflected that mature B cells (FO B, MZ B) predominantly located in the white pulp, while transitional B cells were found in the red pulp (located outside of the white pulp), which facilitates the transportation of transitional B cells through the bloodstream. After defining the configuration, we stained the samples with CDoB and antibodies together (Figures 4B and S13). The results showed that CDoB accurately distinguished the territory of mature B cells from T and transitional B lymphocytes. Importantly, we also demonstrated that SLC25A16 expression was upregulated in mature B cells corresponding to the CDoB intensity (Figure S14). This result clearly emphasizes not only the selectivity of CDoB but also the selectivity of SLC25A16 as a novel biomarker for mature B cells. Moreover, to the best of our knowledge, this is the first case of analyzing the structural splenic tissues with a fluorescent probe, further providing a multidimensional window for cellular analysis.

Figure 4.

Figure 4

B cell development tracking by CDoB. (A) SP tissues were stained with only antibody. (B) CDoB stained the tissue for 4 h, and antibodies were added. The left images were taken by using a 5× objective lens, and the right ones were imaged by a 10× objective lens.

Conclusions

In this study, we introduce the mature B cell-selective probe CDoB, which effectively discriminates between B cell developmental stages of progenitor, transitional, and mature B lymphocytes based on CDoB staining intensity. We elucidated the selective mechanism as GOLD with SLC25A16 overexpressed in mature B lymphocytes through both SLC-CRISPRa and CRISPRi screening. Further validation using the CRISPR-KO technique confirmed that CDoB relies on SLC25A16 as the main gate to localize into mitochondria in mature B cells. The function and substrate of SLC25A16 have not been precisely determined, with only a speculative substrate of coenzyme A, observed in yeast protein with lower homology to the murine protein. Therefore, our findings will further lead to a deep investigation of SLC25A16, and its relationship with B cell maturation.

With promising results, we explored the potential of CDoB to monitor the topical area of mature B lymphocytes in live splenic tissue. Through its superior performance, we identified SLC25A16 as a potential novel marker for mature B lymphocytes. In summary, we propose that both CDoB and SLC25A16 could serve as valuable indicators for monitoring the B cell maturation process. We believe that this research will not only provide a useful index but also shed light on solving complex biological systems using the fluorescent small molecule, CDoB.

Acknowledgments

This research was supported by the Institute for Basic Science (IBS) (IBS-R007-A1 to Y.-T.C. and H.-Y.K.), Basic Science Research Institute Fund (2021R1A6A1A10042944 to Y.-T.C.), the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2023R1A2C300453411 to Y.-T.C.), the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2020R1A2C2009776 to N.-Y.K.; RS-2023-00210972 to H.-Y.K.), and the Ministry of Education (2020R1A6A1A03047902 to N.-Y.K.). H.C. is grateful for financial support from the Hyundai Motor Chung Mong-Koo Foundation.

Glossary

Abbreviations

GOLD

gating-oriented live-cell distinction

LC

luminescent-carbohydrate

DOFL

diversity-oriented fluorescence library

CDoB

compound designation orange for B or old B

SLC

solute carrier

ABC

ATP-binding cassette

NGS

next-generation sequencing

BM

bone marrow

SP

spleen

CyTOF

cytometry by time of flight

T1 B

transitional type 1 B

T2 B

transitional type 2 B

FO B

follicular B

MZ B

marginal zone B

sgRNA

single-guide RNA

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/jacsau.4c00001.

  • Detailed synthetic schemes, experimental procedures, and general information, including NMR spectra; SLC-CRISPR screening and flow cytometry protocols; general information; animal experiments; lymphocyte preparations; flow cytometry-based screening protocol; magnetic-activated cell sorting protocol; image acquisition and localization study; SP tissue imaging protocol; mass cytometry protocol; mass cytometry data analysis method; SLC-CRISPRa/i screening protocols; CRISPR-knockout experiment method; PCR protocols; NMR spectra; and HPLC spectra (PDF)

Author Contributions

H.C. and H.-Y.K. contributed equally to this work. CRediT: Heewon Cho conceptualization, data curation, investigation, methodology, validation, visualization, writing-original draft; Haw-Young Kwon conceptualization, funding acquisition, methodology, writing-review & editing; Youngsook Kim methodology; Kyungwon Kim methodology; Eun Jig Lee methodology; Nam-Young Kang conceptualization, funding acquisition, methodology, supervision; Young-Tae Chang conceptualization, formal analysis, funding acquisition, project administration, supervision, writing-review & editing.

The authors declare no competing financial interest.

Supplementary Material

au4c00001_si_001.pdf (2.4MB, pdf)

References

  1. Pittet M. J.; Garris C. S.; Arlauckas S. P.; Weissleder R. Recording the wild lives of immune cells. Sci. Immunol 2018, 3 (27), eaaq0491 10.1126/sciimmunol.aaq0491. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Kwon H. Y.; Kumar Das R.; Jung G. T.; Lee H. G.; Lee S. H.; Berry S. N.; Tan J. K. S.; Park S.; Yang J. S.; Park S.; et al. Lipid-Oriented Live-Cell Distinction of B and T Lymphocytes. J. Am. Chem. Soc. 2021, 143 (15), 5836–5844. 10.1021/jacs.1c00944. [DOI] [PubMed] [Google Scholar]
  3. Gao M.; Lee S. H.; Das R. K.; Kwon H. Y.; Kim H. S.; Chang Y. T. A SLC35C2 Transporter-Targeting Fluorescent Probe for the Selective Detection of B Lymphocytes Identified by SLC-CRISPRi and Unbiased Fluorescence Library Screening. Angew. Chem., Int. Ed. Engl. 2022, 61 (36), e202202095 10.1002/anie.202202095. [DOI] [PubMed] [Google Scholar]
  4. Elmore S. A. Enhanced histopathology of the spleen. Toxicol Pathol 2006, 34 (5), 648–655. 10.1080/01926230600865523. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. a Melchers F. Checkpoints that control B cell development. J. Clin. Invest. 2015, 125 (6), 2203–2210. 10.1172/JCI78083. [DOI] [PMC free article] [PubMed] [Google Scholar]; b Morgan D.; Tergaonkar V. Unraveling B cell trajectories at single cell resolution. Trends Immunol. 2022, 43 (3), 210–229. 10.1016/j.it.2022.01.003. [DOI] [PubMed] [Google Scholar]
  6. Cambier J. C.; Gauld S. B.; Merrell K. T.; Vilen B. J. B-cell anergy: from transgenic models to naturally occurring anergic B cells?. Nat. Rev. Immunol 2007, 7 (8), 633–643. 10.1038/nri2133. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. a Cariappa A.; Boboila C.; Moran S. T.; Liu H.; Shi H. N.; Pillai S. The recirculating B cell pool contains two functionally distinct, long-lived, posttransitional, follicular B cell populations. J. Immunol 2007, 179 (4), 2270–2281. 10.4049/jimmunol.179.4.2270. [DOI] [PubMed] [Google Scholar]; b Shahaf G.; Zisman-Rozen S.; Benhamou D.; Melamed D.; Mehr R. B Cell Development in the Bone Marrow Is Regulated by Homeostatic Feedback Exerted by Mature B Cells. Front Immunol 2016, 7, 77. 10.3389/fimmu.2016.00077. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Koppenol W. H.; Bounds P. L.; Dang C. V. Otto Warburg’s contributions to current concepts of cancer metabolism. Nat. Rev. Cancer 2011, 11 (5), 325–337. 10.1038/nrc3038. [DOI] [PubMed] [Google Scholar]
  9. Cho H.; Kwon H. Y.; Sharma A.; Lee S. H.; Liu X.; Miyamoto N.; Kim J. J.; Im S. H.; Kang N. Y.; Chang Y. T. Visualizing inflammation with an M1 macrophage selective probe via GLUT1 as the gating target. Nat. Commun. 2022, 13 (1), 5974. 10.1038/s41467-022-33526-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. a Hu X. L.; Gan H. Q.; Qin Z. Y.; Liu Q.; Li M.; Chen D.; Sessler J. L.; Tian H.; He X. P. Phenotyping of Methicillin-Resistant Staphylococcus aureus Using a Ratiometric Sensor Array. J. Am. Chem. Soc. 2023, 145 (16), 8917–8926. 10.1021/jacs.2c12798. [DOI] [PubMed] [Google Scholar]; b Dou W. T.; Wang X.; Liu T. T.; Zhao S. W.; Liu J. J.; Yan Y.; Li J.; Zhang C. Y.; Sedgwick A. C.; Tian H.; et al. A homogeneous high-throughput array for the detection and discrimination of influenza A viruses. Chem-Us 2022, 8 (6), 1750–1761. 10.1016/j.chempr.2022.03.012. [DOI] [Google Scholar]
  11. Lewis S. M.; Williams A.; Eisenbarth S. C. Structure and function of the immune system in the spleen. Sci. Immunol 2019, 4 (33), eaau6085 10.1126/sciimmunol.aau6085. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Kay A. W.; Strauss-Albee D. M.; Blish C. A. Application of Mass Cytometry (CyTOF) for Functional and Phenotypic Analysis of Natural Killer Cells. Methods Mol. Biol. 2016, 1441, 13–26. 10.1007/978-1-4939-3684-7_2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. LeBien T. W.; Tedder T. F. B lymphocytes: how they develop and function. Blood 2008, 112 (5), 1570–1580. 10.1182/blood-2008-02-078071. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Bronte V.; Pittet M. J. The spleen in local and systemic regulation of immunity. Immunity 2013, 39 (5), 806–818. 10.1016/j.immuni.2013.10.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Giacomini K. M.; Huang S. M.; Tweedie D. J.; Benet L. Z.; Brouwer K. L.; Chu X.; Dahlin A.; Evers R.; Fischer V.; et al. Membrane transporters in drug development. Nat. Rev. Drug Discovery 2010, 9 (3), 215–236. 10.1038/nrd3028. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Chavez A.; Tuttle M.; Pruitt B. W.; Ewen-Campen B.; Chari R.; Ter-Ovanesyan D.; Haque S. J.; Cecchi R. J.; Kowal E. J. K.; Buchthal J.; et al. Comparison of Cas9 activators in multiple species. Nat. Methods 2016, 13 (7), 563–567. 10.1038/nmeth.3871. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Gilbert L. A.; Larson M. H.; Morsut L.; Liu Z.; Brar G. A.; Torres S. E.; Stern-Ginossar N.; Brandman O.; Whitehead E. H.; Doudna J. A.; et al. CRISPR-mediated modular RNA-guided regulation of transcription in eukaryotes. Cell 2013, 154 (2), 442–451. 10.1016/j.cell.2013.06.044. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Park S. J.; Kim B.; Choi S.; Balasubramaniam S.; Lee S. C.; Lee J. Y.; Kim H. S.; Kim J. Y.; Kim J. J.; Lee Y. A.; et al. Imaging inflammation using an activated macrophage probe with Slc18b1 as the activation-selective gating target. Nat. Commun. 2019, 10 (1), 1111. 10.1038/s41467-019-08990-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Kunji E. R. S.; King M. S.; Ruprecht J. J.; Thangaratnarajah C. The SLC25 Carrier Family: Important Transport Proteins in Mitochondrial Physiology and Pathology. Physiology (Bethesda) 2020, 35 (5), 302–327. 10.1152/physiol.00009.2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Prohl C.; Pelzer W.; Diekert K.; Kmita H.; Bedekovics T.; Kispal G.; Lill R. The yeast mitochondrial carrier Leu5p and its human homologue Graves’ disease protein are required for accumulation of coenzyme A in the matrix. Mol. Cell. Biol. 2001, 21 (4), 1089–1097. 10.1128/MCB.21.4.1089-1097.2001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Fiermonte G.; Paradies E.; Todisco S.; Marobbio C. M.; Palmieri F. A novel member of solute carrier family 25 (SLC25A42) is a transporter of coenzyme A and adenosine 3′,5′-diphosphate in human mitochondria. J. Biol. Chem. 2009, 284 (27), 18152–18159. 10.1074/jbc.M109.014118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Mensah F. F. K.; Armstrong C. W.; Reddy V.; Bansal A. S.; Berkovitz S.; Leandro M. J.; Cambridge G. CD24 Expression and B Cell Maturation Shows a Novel Link With Energy Metabolism: Potential Implications for Patients With Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Front Immunol 2018, 9, 2421. 10.3389/fimmu.2018.02421. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

au4c00001_si_001.pdf (2.4MB, pdf)

Articles from JACS Au are provided here courtesy of American Chemical Society

RESOURCES