Jicong Cao
Massachusetts Institute of Technology
Network
Latest external collaboration on country level. Dive into details by clicking on the dots.
Publication
Featured researches published by Jicong Cao.
Nature Nanotechnology | 2017
Markita P. Landry; Hiroki Ando; Allen Chen; Jicong Cao; Vishal Isaac Kottadiel; Linda Chio; Darwin Yang; Juyao Dong; Timothy K. Lu; Michael S. Strano
A distinct advantage of nanosensor arrays is their ability to achieve ultralow detection limits in solution by proximity placement to an analyte. Here, we demonstrate label-free detection of individual proteins from Escherichia coli (bacteria) and Pichia pastoris (yeast) immobilized in a microfluidic chamber, measuring protein efflux from single organisms in real time. The array is fabricated using non-covalent conjugation of an aptamer-anchor polynucleotide sequence to near-infrared emissive single-walled carbon nanotubes, using a variable chemical spacer shown to optimize sensor response. Unlabelled RAP1 GTPase and HIV integrase proteins were selectively detected from various cell lines, via large near-infrared fluorescent turn-on responses. We show that the process of E. coli induction, protein synthesis and protein export is highly stochastic, yielding variability in protein secretion, with E. coli cells undergoing division under starved conditions producing 66% fewer secreted protein products than their non-dividing counterparts. We further demonstrate the detection of a unique protein product resulting from T7 bacteriophage infection of E. coli, illustrating that nanosensor arrays can enable real-time, single-cell analysis of a broad range of protein products from various cell types.
Nature Communications | 2018
Jicong Cao; Pablo Perez-Pinera; Ky Lowenhaupt; Ming Ru Wu; Oliver Purcell; César de la Fuente-Núñez; Timothy K. Lu
Current limitations to on-demand drug manufacturing can be addressed by technologies that streamline manufacturing processes. Combining the production of two or more drugs into a single batch could not only be useful for research, clinical studies, and urgent therapies but also effective when combination therapies are needed or where resources are scarce. Here we propose strategies to concurrently produce multiple biologics from yeast in single batches by multiplexing strain development, cell culture, separation, and purification. We demonstrate proof-of-concept for three biologics co-production strategies: (i) inducible expression of multiple biologics and control over the ratio between biologic drugs produced together; (ii) consolidated bioprocessing; and (iii) co-expression and co-purification of a mixture of two monoclonal antibodies. We then use these basic strategies to produce drug mixtures as well as to separate drugs. These strategies offer a diverse array of options for on-demand, flexible, low-cost, and decentralized biomanufacturing applications without the need for specialized equipment.The ability to combine the production of multiple biologics into a single ‘on demand’ system could help in situations where resources are limited. Here the authors demonstrate a proof-of-concept approach for the co-production of three biologics, allowing singular, mixed and combination drug products.
Molecular Cell | 2017
Ying-Chou Chen; Fahim Farzadfard; Nava Gharaei; William W. Chen; Jicong Cao; Timothy K. Lu
The genome-wide perturbation of transcriptional networks with CRISPR-Cas technology has primarily involved systematic and targeted gene modulation. Here, we developed PRISM (Perturbing Regulatory Interactions by Synthetic Modulators), a screening platform that uses randomized CRISPR-Cas transcription factors (crisprTFs) to globally perturb transcriptional networks. By applying PRISM to a yeast model of Parkinsons disease (PD), we identified guide RNAs (gRNAs) that modulate transcriptional networks and protect cells from alpha-synuclein (αSyn) toxicity. One gRNA identified in this screen outperformed the most protective suppressors of αSyn toxicity reported previously, highlighting PRISMs ability to identify modulators of important phenotypes. Gene expression profiling revealed genes differentially modulated by this strong protective gRNA that rescued yeast from αSyn toxicity when overexpressed. Human homologs of top-ranked hits protected against αSyn-induced cell death in a human neuronal PD model. Thus, high-throughput and unbiased perturbation of transcriptional networks via randomized crisprTFs can reveal complex biological phenotypes and effective disease modulators.
ACS Synthetic Biology | 2018
Jicong Cao; César de la Fuente-Núñez; Rui Wen Ou; Marcelo D. T. Torres; Santosh G. Pande; Anthony J. Sinskey; Timothy K. Lu
Antibiotic resistance is one of the most challenging global health threats in our society. Antimicrobial peptides (AMPs) represent promising alternatives to conventional antibiotics for the treatment of drug-resistant infections. However, they are limited by their high manufacturing cost. Engineering living organisms represents a promising approach to produce such molecules in an inexpensive manner. Here, we genetically modified the yeast Pichia pastoris to produce the prototypical AMP apidaecin Ia using a fusion protein approach that leverages the beneficial properties ( e.g., stability) of human serum albumin. The peptide was successfully isolated from the fusion protein construct, purified, and demonstrated to have bioactivity against Escherichia coli. To demonstrate this approach as a manufacturing solution to AMPs, we scaled-up production in bioreactors to generate high AMP yields. We envision that this system could lead to improved AMP biomanufacturing platforms.
bioRxiv | 2018
Fahim Farzadfard; Nava Gharaei; Yasutomi Higashikuni; Giyoung Jung; Jicong Cao; Timothy K. Lu
Computing and memory in living cells are central to encoding next-generation therapies and studying in situ biology, but existing strategies have limited encoding capacity and are challenging to scale. To overcome this bottleneck, we developed a highly scalable, robust and compact platform for encoding logic and memory operations in living bacterial and human cells. This platform, named DOMINO for DNA-based Ordered Memory and Iteration Network Operator, converts DNA in living cells into an addressable, readable, and writable computation and storage medium via a single-nucleotide resolution read-write head that enables dynamic and highly efficient DNA manipulation. We demonstrate that the order and combination of DNA writing events can be programmed by biological cues and multiple molecular recorders can be coordinated to encode a wide range of order-independent, sequential, and temporal logic and memory operations. Furthermore, we show that these operators can be used to perform both digital and analog computation, and record signaling dynamics and cellular states in a long-term, autonomous, and minimally disruptive fashion. Finally, we show that the platform can be functionalized with gene regulatory modules and interfaced with cellular circuits to continuously monitor cellular phenotypes and engineer gene circuits with artificial learning capacities. We envision that highly scalable, compact, and modular DOMINO operators will lay the foundation for building robust and sophisticated synthetic gene circuits for numerous biotechnological and biomedical applications. One Sentence Summary A programmable read-write head with single-nucleotide-resolution for genomic DNA enables robust and scalable computing and memory operations in living cells.
ACS Synthetic Biology | 2018
Oliver Purcell; Jicong Cao; Isaak Mueller; Ying-Chou Chen; Timothy K. Lu
RNA interference (RNAi) is widely used as a research tool for studying biological systems and implementing artificial genetic circuits that function by modulating RNA concentrations. Here we engineered Saccharomyces cerevisiae containing a heterologous Saccharomyces castelli RNAi system as a test-bed for RNAi-based circuits. Unlike prior approaches, we describe a strategy that leverages repeat-structured siRNA precursors with incrementally sized stems formed from 23 bp-repeats to achieve modular RNAi-based gene regulation. These enable repression strength to be tuned in a systematic manner by changing the size of the siRNA precursor hairpin stem, without modifying the number or sequence of target sites in the target RNA. We demonstrate that this hairpin-based regulation is able to target both cytoplasmic and nuclear localized RNAs and is stable over extended growth periods. This platform enables the targeting of cellular RNAs as a tunable regulatory layer for sophisticated gene circuits in Saccharomyces cerevisiae.
ACS Synthetic Biology | 2017
Oliver Purcell; Patrick Opdensteinen; William W. Chen; Ky Lowenhaupt; Alexander Brown; Mario Hermann; Jicong Cao; Niklas Tenhaef; Eric Kallweit; Robin Kastilan; Anthony J. Sinskey; Pablo Perez-Pinera; Johannes F. Buyel; Timothy K. Lu
Colloid and Interface Science Communications | 2018
César de la Fuente-Núñez; Paul Brown; Marcelo Der Torossian Torres; Jicong Cao; Timothy K. Lu
Archive | 2018
Lu, Timothy, Kuan-Ta; Pablo Perez-Pinera; Jicong Cao; Oliver Purcell
School of Chemistry, Physics & Mechanical Engineering; Science & Engineering Faculty | 2017
Anthony Verderosa; César de la Fuente-Núñez; Sarah C. Mansour; Jicong Cao; Timothy K. Lu; Robert E. W. Hancock; Kathryn E. Fairfull-Smith