[Google Scholar] [PubMed]

Selected Publications

1. Ma, S., Zhang, B., LaFave L., Chiang, Z., Hu Y., Ding, J., Brack, A., Kartha, V., Law, T., Lareau C., Hsu, Y.C., Regev, A. & Buenrostro, J. Chromatin potential identified by shared single-cell profiling of RNA and chromatin. Cell, 183, 1103-1116 (2020).
   • SHARE-seq for open chromatin & RNA co-profiling
   • “Chromatin Potential” for predicting cell fate choice during skin differentiation
   • Featured in Nature Reviews Genetics “SHARE-seq reveals chromatin potential”
   • Featured in RNA-SEQ “SHARE-seq – measurement of chromatin accessibility and gene expression in the same single cell”
2. Ma, S., Revenga, M., Sun, Z., Sun, C., Murphy, T. W., Xie, H., González-Maeso, J. & Lu. C. Cell-type-specific brain methylomes profiled via ultralow-input microfluidics. Nature Biomedical Engineering, 2, 183-194 (2018).
   • Microfluidic devices for low-input and single cell genome-wide DNA methylation profiling
   • Featured in VT news “Epigenomic tool breakthrough has implications for identifying disease processes”
   • Featured in Behind-the-paper “Using microfluidics to map brain epigenomes”
   • Featured in Nature Biomedical Engineering “Epigenetic profiling with ultralow DNA amounts”
3. Ma, S., Hsieh, Y., Ma, J. & Lu, C. Low-input and multiplexed microfluidic assay reveals epigenomic variation across cerebellum and prefrontal cortex (SurfaceChIP-seq). Science Advances, 4, eaar8187 (2018).
   • Microfluidic technology for low-input ChIP-seq
   • Featured in GenomeWeb “Virginia tech team develops microfluidic technique for low-input ChIP-seq”
4. Zhang, Q., Ma, S. Liu, Z., Zhu, B., Zhou, Z., Li, G., Meana, J. J., González-Maeso, J., Lu, C. Droplet-based bisulfite sequencing for high-throughput profiling of single-cell DNA methylomes. Nature Communications, 14, 4672 (2023).
   • High-throughput single-cell DNA methylation profiling technology
5. Joung, J., Ma, S.*, Tay, T.* Geiger-Schuller, K.R.*, Kirchgatterer, P.C., Verdine, V.K., Guo, B. Arias-Garcia, A.A., E. Allen, W. E., Singh, A., Kuksenko, O., Abudayyeh, O. O., Gootenberg, J. S., Fu, Z., Macrae, R.K., Buenrostro, J.D., Regev, A. & Zhang, Z. A transcription factor atlas of directed differentiation. Cell, 186, 209-229 (2023).
   • Massive screening of every single TF in hESCs
6. Deng, Y., Bartosovic, M., Ma, S., Zhang, D., Kukanja, P., Xiao, Y., Su, G., Liu, Y., Qin, X., Rosoklija, G.B., Dwork, A.J., Mann, J.J., Xu, M.L., Halene, S., Craft, J.E., Leong, K.W., Boldrini, M., Castelo-Branco, G. & Fan, R. Spatial profiling of chromatin accessibility in mouse and human tissues. Nature, 609, 375–383 (2022).
   • Spatial epigenomic technology
   • Highlighted in Nature Structural & Molecular Biology “Chromatin found in space“
7. Kartha V., Duarte F., Hu Y., Ma, S. Chew, J., Lareau, C., Earl, A., Burkett, Z., Kohlway, A., Lebofsky, R. & Buenrostro. J. Functional Inference of Gene Regulation using Single-Cell Multi-Omics. Cell Genomics, 2, 100166 (2022).
8. Yuan, W., Ma, S., Brown, J., Kim, K., Murek, V., Trastulla, L., Meissner, A., Lodato, S., Shetty, A., Levin, J., Buenrostro, J., Ziller, M. & Arlotta, P. Temporally-Divergent Regulatory Mechanisms Govern Neuronal Development and Diversification in the Neocortex. Nature Neuroscience, 25, 1049–1058 (2022).
   • Transcriptomic and epigenomic diversity at single-cell level in mouse and marmoset brain
9. Concepcion, C., Ma, S., Bhutkar, A., Liu, M., DeAngelo, L.P., Kim, J.Y., Priore, I.D., Schoenfeld, A.J., Miller, M., Kartha, V.K., Westcott, P.M.K., Sánchez-Rivera, F.J., Meli, K., Gupta, M., Bronson, R.T., Riely, G.J., Rekhtman, N., Rudin, C.M., Kim, C.F., Regev, A., Buenrostro J.B. & Jacks, T. Smarca4 inactivation promotes lineage-specific transformation and early metastatic features in the lung. Cancer Discovery, 12(2), 562-585 (2021).
   • Genetic mutation increases lung tumor burden in mouse and human patients
10. Choi, S., Zhang, B., Ma, S., Gonzalez-Celeiro, M., Stein, D., Jin, X., Kim, S.T., Kang, Y-L, Besnard, A., Rezza, A., Grisanti, L., Buenrostro, J.D. Rendl, M., Nahrendorf, M., Sahay, A. & Hsu, Y-C. Corticosterone inhibits GAS6 to govern hair follicle stem-cell quiescence. Nature, 592, 428–432 (2021).
    • Hair loss due to chronic stress
    • Featured in Nature “Relax to grow more hair”
    • Featured in Harvard News “How chronic stress leads to hair loss”
    • Featured in ScienceDaily and many others
11. Zhang, B., Ma, S., Rachmin, I., He, M., Baral, P., Choi, S., Gonçalves, W.A., Shwartz, Y., Fast, E.M., Su, Y., Zon, L.I., Regev, A., Buenrostro, J.D., Cunha, T.M., Chiu, I.M., Fisher, D.E. & Hsu, Y.C. Hyperactivation of sympathetic nerves drives depletion of melanocyte stem cells. Nature, 577, 676-681 (2020).
    • Hair greying under acute stress
    • Featured in Nature “How the stress of fight or flight turns hair white”
    • Featured in >200 news websites
    • Ranked 36th of the 302,805 tracked articles by online attention
12. LaFave, L., Kartha, V.*, Ma, S.*, Meli, K., Priore, I.D., Lareau, C., Naranjo, S., Westcott, P.M.K., Duarte, F.M., Sankar, V., Chiang, Z., Brack, A., Law, T., Hauck, H., Okimoto, A., Regev, A., Buenrostro, J.D. & Jacks, T. Epigenomic state transitions characterize tumor progression in lung adenocarcinoma. Cancer Cell, 38, 212-228, (2020). (* equal contribution)
    • Epigenomic regulators in lung tumor progression 
    • Featured in MIT news “Gene-controlling mechanisms play key role in cancer progression”
    • Featured in ScienceDaily
    • Featured in Cancer Cell
13. Lareau, C., Ma, S., Duarte F., & Buenrostro J. Inference and effects of barcode multiplets in droplet-based single-cell assays. Nature Communications, 11, 866 (2020).
    • Computational identification of doublets in single-cell sequencing data

Patents

1. Buenrostro, J., Ma, S., Regev, A., Methods and Compositions for Analyzing Nucleic Acids.
2. Lu, C., Ma, S., Methods and Devices for Analysis of Nucleic Acids from Cells.

bioRxiv

1. Yan, H. Ma, S., Kartha, V. et al. Single-cell multi-scale footprinting reveals the modular organization of DNA regulatory elements. bioRxiv (2023)

Additional Publications

1. Ma, S., Regev, A. & Buenrosto, J. SHARE-seq V1. Protocols.io (2021).
2. Del Priore, I.*, Ma, S.*, Strecker, J., Jacks, T., LaFave, L. & Buenrosto, J. Protocol for single-cell ATAC-sequencing using combinatorial indexing. STAR protocols, 100583 (2021). (* equal contribution) 
3. Ma, S., Murphy, T. W. & Lu, C. Microfluidics for genome-wide studies involving next generation sequencing.Biomicrofluidics, 11, 021501 (2017). (review)
   •  Selected as Editor’s Picks
4. Ma, S., Bryson, B.D., Sun, C., Fortune, S. M. & Lu, C. RNA extraction from a mycobacterium under ultrahigh electric field intensity. Analytical Chemistry, 88, 5053-5057 (2016).
5. Ma, S., Loufakis, D. N., Cao Z., Chang Y., Achenie, L. EK & Lu C. Diffusion-based microfluidic PCR for “one-pot” analysis of cells. Lab on a Chip, 14, 2905-2909 (2014).
   •  Selected as hot article
   •  Selected as cover
6. Ma, S., Schroeder, B., Sun, C., Loufakis, D. N., Cao, Z. Sriranganathan, N. & Lu, C. Electroporation-based delivery of cell-penetrating peptide conjugates of peptide nucleic acids for antisense inhibition of intracellular bacteria. Integrative Biology, 2014, 973-978 (2014).
7. Ma, S., Tang, Y., Liu, J. & Wu, J. Visible paper chip immunoassay for rapid determination of bacteria in water distribution system. Talanta, 120, 135-140 (2014). 
8. Thakore, P., Schnell, A., Zhao, M., Huang, L., Hou, Y., Christian, E., Zaghouani, S., Wang, C., Singh, V., Ma, S. et al. The chromatin landscape of Th17 cells reveals mechanisms of diversification of regulatory and pro-inflammatory states. Nature Immunology, accepted (2024)
9. Cheong, J.G.*, Ravishankar A.*, Sharma, S.*, Parkhurst, C.*, Grassmann, S., Wingert, C.K.,  Laurent, P., Ma, S. et al. Epigenetic Memory of COVID-19 in Innate Immune Cells and Their Progenitors. Cell, 186 (18), 3882-3902 (2023).
10. Otto, J.E., Ursu, O., Wu, A.P., Winter, E.B., Cuoco, M.S. Ma, S., Qian, K., Michel, B.C., Buenrostro, J.D., Berger, B., Regev, A. & Kadoch, C. Structural and functional properties of mSWI/SNF chromatin remodeling complexes revealed through single-cell perturbation screens. Molecular Cell, 83, 1–18 (2023)
11. Zhang, D. , Deng, Y. , Kukanja, P. , Agirre, E., Bartosovic, M., Dong, M., Ma C., Ma, S. et al. Spatial epigenome–transcriptome co-profiling of mammalian tissues. Nature, 616, 113–122 (2023).
12. Hsieh, Y.P., Naler, L., Ma, S. & Lu C. Cell-type-specific epigenomic variations associated with BRCA1 mutation in pre-cancer human breast tissues. NAR Genomics and Bioinformatics, 4, lqac006 (2021). 
13. Biancala, T., Scalia, G., Buffoni, L., Avasthi, R., Lu, Z., Sanger A., Tokcan, N., Vanderburg, C., Segerstolpe, A., Zhang M., Avraham-Davidi, I., Vickovic, S., Nitzan, M., Ma, S. et al. Deep learning and alignment of spatially resolved single-cell transcriptomes with Tangram. Nature Methods, 18, 1352–1362 (2021).
14. Avagyan, S., Weber, M.C., Ma, S., Prasad, M., Mannherz, W.P., Yang, S., Buenrostro, J.D., and Zon, L.I. Single-cell ATAC-seq reveals GATA2-dependent priming defect in myeloid and a maturation bottleneck in lymphoid lineages. Blood Advances, 5, 2673-2686 (2021).
15. Li, Q., Meissner, T., Wang, F., Du, Z., Ma, S., Kshirsagar, S., Tilburgs, T., Buenrostro, J., Uesugi, M., & Strominger, J. ELF3 activated by a superenhancer and an autoregulatory feedback loop is required for high-level HLA-C expression on extravillous trophoblasts. PNAS, 118, e2025512118 (2021)
16. Sarikhani, M., Garbern, J., Ma S., et al. Sustained activation of ampk enhances differentiation of human iPSC-derived cardiomyocytes via sirtuin activation. Stem Cell Report, 20, 498-514, (2020).
17. Xu, H., Ding, J., Porter, C., Wallrapp, A., Tabaka, M., Ma, S. et al. Transcriptional atlas of intestinal immune cells reveals that neuropeptide α-cgrp modulates group 2 innate lymphoid cell responses. Immunity, 51, 696-708 (2019).
18. Sarma, M., Lee, J., Ma, S., Li, S. & Lu, C. A diffusion-based microfluidic device for single-cell RNA-seq. Lab on a Chip, 19, 1247-1256 (2019).
19. Murphy, T. W., Zhang, Q., Naler, L., Ma, S. & Lu, C. Recent advances on microfluidic technologies for single cell analysis. Analyst, 143, 60-80 (2018). (review)
20. Murphy, T. W., Hsieh Y., Ma, S., Zhu, Y. & Lu, C. Microfluidic low-Input fluidized-bed enabled ChIP-seq device for automated and parallel analysis of histone modifications. Analytical Chemistry, 90, 7666-7674 (2018).
21. Sun, C., Hsieh, Y., Ma, S., Geng, S., Cao, Z., Li, L. & Lu, C. Immunomagnetic separation of tumor initiating cells by screening two surface markers. Scientific Reports, 7, 40632 (2017).
22. Sun, C., Hassanisaber, H., Yu, R., Ma, S., Verbridge, S. S. & Lu, C. Paramagnetic structures within a microfluidic channel for enhanced immunomagnetic isolation and surface patterning of cells. Scientific Reports, 6, 29407 (2016).
23. Crowa, J., Achenie, L. E. K., Lu, C., Ma, S., Loufakis, D. N. Cao, Z. & Chang, Y. Optimal design of microfluidic platforms for diffusion-based PCR for “one-pot” analysis of cells. Computer Aided Chemical Engineering, 37, 1199-1204 (2015).
24. Loufakis, D.N., Cao, Z., Ma, S., Mittelman, D. & Lu, C. Focusing of mammalian cells under an ultrahigh pH gradient created by unidirectional electropulsation in a confined microchamber. Chemical Science, 5, 3331-3337 (2014).
25. Sun, C., Ouyang M., Cao, Z., Ma, S., Alqublan, H., Sriranganathan, N., Wang, Y. & Lu, C. Electroporation-delivered fluorescent protein biosensors for probing molecular activities in cells without genetic encoding. Chemical Communications, 50, 11536-11539 (2014). 
26. Tan, J., Zhao W., Yu J., Ma, S., Sailor, M. J. & Wu, J. Capture, enrichment, and mass spectrometric detection of low‐molecular‐weight biomarkers with nanoporous silicon microparticles. Advanced Healthcare Materials, 1, 742-750 (2012).
27. Liu, Z., Wu, Q., Song, X. & Ma, S. Solid high-proton conductors based on heteropoly acids. Progress in Chemistry, 21, 982-989 (2009).