Scalable and automated CRISPR-based strain engineering using droplet microfluidics

Precision oncology revolution: CRISPR-Cas9 and PROTAC technologies unleashed

Cancer continues to present a substantial global health challenge, with its incidence and mortality rates persistently reflecting its significant impact. The emergence of precision oncology has provided a breakthrough in targeting oncogenic drivers previously deemed "undruggable" by conventional therapeutics and by limiting off-target cytotoxicity. Two groundbreaking technologies that have revolutionized the field of precision oncology are primarily CRISPR-Cas9 gene editing and more recently PROTAC (PROteolysis TArgeting Chimeras) targeted protein degradation technology. CRISPR-Cas9, in particular, has gained widespread recognition and acclaim due to its remarkable ability to modify DNA sequences precisely. Rather than editing the genetic code, PROTACs harness the ubiquitin proteasome degradation machinery to degrade proteins of interest selectively. Even though CRISPR-Cas9 and PROTAC technologies operate on different principles, they share a common goal of advancing precision oncology whereby both approaches have demonstrated remarkable potential in preclinical and promising data in clinical trials. CRISPR-Cas9 has demonstrated its clinical potential in this field due to its ability to modify genes directly and indirectly in a precise, efficient, reversible, adaptable, and tissue-specific manner, and its potential as a diagnostic tool. On the other hand, the ability to administer in low doses orally, broad targeting, tissue specificity, and controllability have reinforced the clinical potential of PROTAC. Thus, in the field of precision oncology, gene editing using CRISPR technology has revolutionized targeted interventions, while the emergence of PROTACs has further expanded the therapeutic landscape by enabling selective protein degradation. Rather than viewing them as mutually exclusive or competing methods in the field of precision oncology, their use is context-dependent (i.e., based on the molecular mechanisms of the disease) and they potentially could be used synergistically complementing the strengths of CRISPR and vice versa. Herein, we review the current status of CRISPR and PROTAC designs and their implications in the field of precision oncology in terms of clinical potential, clinical trial data, limitations, and compare their implications in precision clinical oncology.

Automated in vivo enzyme engineering accelerates biocatalyst optimization

Achieving cost-competitive bio-based processes requires development of stable and selective biocatalysts. Their realization through in vitro enzyme characterization and engineering is mostly low throughput and labor-intensive. Therefore, strategies for increasing throughput while diminishing manual labor are gaining momentum, such as in vivo screening and evolution campaigns. Computational tools like machine learning further support enzyme engineering efforts by widening the explorable design space. Here, we propose an integrated solution to enzyme engineering challenges whereby ML-guided, automated workflows (including library generation, implementation of hypermutation systems, adapted laboratory evolution, and in vivo growth-coupled selection) could be realized to accelerate pipelines towards superior biocatalysts.

"Cell Disk" DNA Storage System Capable of Random Reading and Rewriting

DNA has emerged as an appealing material for information storage due to its great storage density and durability. Random reading and rewriting are essential tasks for practical large-scale data storage. However, they are currently difficult to implement simultaneously in a single DNA-based storage system, strongly limiting their practicability. Here, a "Cell Disk" storage system is presented, achieving high-density in vivo DNA data storage that enables both random reading and rewriting. In this system, each yeast cell is used as a chamber to store information, similar to a "disk block" but with the ability to self-replicate. Specifically, each genome of yeast cell has a customized CRISPR/Cas9-based "lock-and-key" module inserted, which allows selective retrieval, erasure, or rewriting of the targeted cell "block" from a pool of cells ("disk"). Additionally, a codec algorithm with lossless compression ability is developed to improve the information density of each cell "block". As a proof of concept, target-specific reading and rewriting of the compressed data from a mimic cell "disk" comprising up to 105 "blocks" are demonstrated and achieve high specificity and reliability. The "Cell Disk" system described here concurrently supports random reading and rewriting, and it should have great scalability for practical data storage use.

Microfluidics: a concise review of the history, principles, design, applications, and future outlook

Microfluidic technologies have garnered significant attention due to their ability to rapidly process samples and precisely manipulate fluids in assays, making them an attractive alternative to conventional experimental methods. With the potential for revolutionary capabilities in the future, this concise review provides readers with insights into the fascinating world of microfluidics. It begins by introducing the subject's historical background, allowing readers to familiarize themselves with the basics. The review then delves into the fundamental principles, discussing the underlying phenomena at play. Additionally, it highlights the different aspects of microfluidic device design, classification, and fabrication. Furthermore, the paper explores various applications, the global market, recent advancements, and challenges in the field. Finally, the review presents a positive outlook on trends and draws lessons to support the future flourishing of microfluidic technologies.

Enabling pathway design by multiplex experimentation and machine learning

The remarkable metabolic diversity observed in nature has provided a foundation for sustainable production of a wide array of valuable molecules. However, transferring the biosynthetic pathway to the desired host often runs into inherent failures that arise from intermediate accumulation and reduced flux resulting from competing pathways within the host cell. Moreover, the conventional trial and error methods utilized in pathway optimization struggle to fully grasp the intricacies of installed pathways, leading to time-consuming and labor-intensive experiments, ultimately resulting in suboptimal yields. Considering these obstacles, there is a pressing need to explore the enzyme expression landscape and identify the optimal pathway configuration for enhanced production of molecules. This review delves into recent advancements in pathway engineering, with a focus on multiplex experimentation and machine learning techniques. These approaches play a pivotal role in overcoming the limitations of traditional methods, enabling exploration of a broader design space and increasing the likelihood of discovering optimal pathway configurations for enhanced production of molecules. We discuss several tools and strategies for pathway design, construction, and optimization for sustainable and cost-effective microbial production of molecules ranging from bulk to fine chemicals. We also highlight major successes in academia and industry through compelling case studies.

An outlook on the current challenges and opportunities in DNA data storage

Silicon is the gold standard for information storage systems. The exponential generation of digital information will exhaust the global supply of refined silicon. Therefore, investing in alternative information storage materials such as DNA has gained momentum. DNA as a memory material possesses several advantages over silicon-based data storage, including higher storage capacity, data retention, and lower operational energy. Routine DNA data storage approaches encode data into chemically synthesized nucleotide sequences. The scalability of DNA data storage depends on factors such as the cost and the generation of hazardous waste during DNA synthesis, latency of writing and reading, and limited rewriting capacity. Here, we review the current status of DNA data storage encoding, writing, storing, retrieving and reading, and discuss the technology's challenges and opportunities.

Recent Advances on Cell Culture Platforms for In Vitro Drug Screening and Cell Therapies: From Conventional to Microfluidic Strategies

The clinical translations of drugs and nanomedicines depend on coherent pharmaceutical research based on biologically accurate screening approaches. Since establishing the 2D in vitro cell culture method, the scientific community has improved cell-based drug screening assays and models. Those advances result in more informative biochemical assays and the development of 3D multicellular models to describe the biological complexity better and enhance the simulation of the in vivo microenvironment. Despite the overall dominance of conventional 2D and 3D cell macroscopic culture methods, they present physicochemical and operational challenges that impair the scale-up of drug screening by not allowing a high parallelization, multidrug combination, and high-throughput screening. Their combination and complementarity with microfluidic platforms enable the development of microfluidics-based cell culture platforms with unequivocal advantages in drug screening and cell therapies. Thus, this review presents an updated and consolidated view of cell culture miniaturization's physical, chemical, and operational considerations in the pharmaceutical research scenario. It clarifies advances in the field using gradient-based microfluidics, droplet-based microfluidics, printed-based microfluidics, digital-based microfluidics, SlipChip, and paper-based microfluidics. Finally, it presents a comparative analysis of the performance of cell-based methods in life research and development to achieve increased precision in the drug screening process.

Recent advances in the use of the CRISPR-Cas system for the detection of infectious pathogens

Infectious diseases cause great economic loss and individual and even social anguish. Existing detection methods lack sensitivity and specificity, have a poor turnaround time, and are dependent on expensive equipment. In recent years, the clustered regularly interspaced short palindromic repeats (CRISPR)‍-CRISPR-associated protein (Cas) system has been widely used in the detection of pathogens that cause infectious diseases owing to its high specificity, sensitivity, and speed, and good accessibility. In this review, we discuss the discovery and development of the CRISPR-Cas system, summarize related analysis and interpretation methods, and discuss the existing applications of CRISPR-based detection of infectious pathogens using Cas proteins. We conclude the challenges and prospects of the CRISPR-Cas system in the detection of pathogens.