ABSTRACT
Functional analysis of non-coding variants associated with human congenital disorders remains challenging due to the lack of efficient in vivo models. Here we introduce dual-enSERT, a robust Cas9-based two-color fluorescent reporter system which enables rapid, quantitative comparison of enhancer allele activities in live mice of any genetic background. We use this new technology to examine and measure the gain- and loss-of-function effects of enhancer variants linked to limb polydactyly, autism, and craniofacial malformation. By combining dual-enSERT with single-cell transcriptomics, we characterize variant enhancer alleles at cellular resolution, thereby implicating candidate molecular pathways in pathogenic enhancer misregulation. We further show that independent, polydactyly-linked enhancer variants lead to ectopic expression in the same cell populations, indicating shared genetic mechanisms underlying non-coding variant pathogenesis. Finally, we streamline dual-enSERT for analysis in F0 animals by placing both reporters on the same transgene separated by a synthetic insulator. Dual-enSERT allows researchers to go from identifying candidate enhancer variants to analysis of comparative enhancer activity in live embryos in under two weeks.
ABSTRACT
Sickle cell disease (SCD) is an inherited hematological disorder associated with high mortality rates, particularly in sub-Saharan Africa. SCD arises due to the polymerization of sickle hemoglobin, which reduces flexibility of red blood cells (RBCs), causing blood vessel occlusion and leading to severe morbidity and early mortality rates if untreated. While sickle solubility tests are available to sub-Saharan African population as a means for detecting sickle hemoglobin (HbS), the test falls short in assessing the severity of the disease and visualizing the degree of cellular deformation. Here, we propose use of holographic cytometry (HC), a high throughput, label-free imaging modality, for comprehensive morphological profiling of RBCs as a means to detect SCD. For this study, more than 2.5 million single-cell holographic images from normal and SCD patient samples were collected using the HC system. We have developed an approach for specially defining training data to improve machine learning classification. Here, we demonstrate the deep learning classifier developed using this approach can produce highly accurate classification, even on unknown patient samples.
Subject(s)
Anemia, Sickle Cell , Deep Learning , Hematologic Diseases , Humans , Hemoglobin, Sickle , Anemia, Sickle Cell/diagnosis , ErythrocytesABSTRACT
Optical methods for examining cellular structure based on endogenous contrast rely on analysis of refractive index changes to discriminate cell phenotype. These changes can be visualized using techniques such as phase contrast microscopy, detected by light scattering, or analyzed numerically using quantitative phase imaging. The statistical variations of refractive index at the nanoscale can be quantified using disorder strength, a metric seen to increase with neoplastic change. In contrast, the spatial organization of these variations is typically characterized using a fractal dimension, which is also seen to increase with cancer progression. Here, we seek to link these two measurements using multiscale measurements of optical phase to calculate disorder strength and in turn to determine the fractal dimension of the structures. First, quantitative phase images are analyzed to show that the disorder strength metric changes with resolution. The trend of disorder strength with length scales is analyzed to determine the fractal dimension of the cellular structures. Comparison of these metrics is presented for different cell lines with varying phenotypes including MCF10A, MCF7, BT474, HT-29, A431, and A549 cell lines, in addition to three cell populations with modified phenotypes. Our results show that disorder strength and fractal dimension can both be obtained with quantitative phase imaging and that these metrics can independently distinguish between different cell lines. Furthermore, their combined use presents a new approach for better understanding cellular restructuring during different pathways.
Subject(s)
Cell Line, Tumor , Fractals , Microscopy, Phase-Contrast , Cell Line, Tumor/cytology , Humans , PhenotypeABSTRACT
Cell-free protein synthesis has emerged as a powerful approach for expanding the range of genetically encoded chemistry into proteins. Unfortunately, efforts to site-specifically incorporate multiple non-canonical amino acids into proteins using crude extract-based cell-free systems have been limited by release factor 1 competition. Here we address this limitation by establishing a bacterial cell-free protein synthesis platform based on genomically recoded Escherichia coli lacking release factor 1. This platform was developed by exploiting multiplex genome engineering to enhance extract performance by functionally inactivating negative effectors. Our most productive cell extracts enabled synthesis of 1,780 ± 30 mg/L superfolder green fluorescent protein. Using an optimized platform, we demonstrated the ability to introduce 40 identical p-acetyl-L-phenylalanine residues site specifically into an elastin-like polypeptide with high accuracy of incorporation ( ≥ 98%) and yield (96 ± 3 mg/L). We expect this cell-free platform to facilitate fundamental understanding and enable manufacturing paradigms for proteins with new and diverse chemistries.
Subject(s)
Amino Acids/chemistry , Escherichia coli Proteins/chemistry , Escherichia coli/metabolism , Peptide Termination Factors/chemistry , Cell-Free System , Codon , Escherichia coli Proteins/genetics , Genetic Engineering , Genome, Bacterial , Green Fluorescent Proteins/metabolism , Mass Spectrometry , Mutation , Peptide Termination Factors/genetics , Peptides/metabolism , Phenylalanine/metabolism , Plasmids/metabolism , Protein BiosynthesisABSTRACT
Chinese Hamster Ovary (CHO) cells are routinely optimized to stably express monoclonal antibodies (mAbs) at high titers. At the early stages of lead isolation and optimization, hundreds of sequences for the target protein of interest are screened. Typically, cell-based transient expression technology platforms are used for expression screening, but these can be time- and resource-intensive. Here, we have developed a cell-free protein synthesis (CFPS) platform utilizing a commercially available CHO extract for the rapid in vitro synthesis of active, aglycosylated mAbs. Specifically, we optimized reaction conditions to maximize protein yields, established an oxidizing environment to enable disulfide bond formation, and demonstrated the importance of temporal addition of heavy chain and light chain plasmids for intact mAb production. Using our optimized platform, we demonstrate for the first time to our knowledge the cell-free synthesis of biologically active, intact mAb at >100 mg/L using a eukaryotic-based extract. We then explored the utility of our system as a tool for ranking yields of candidate antibodies. Unlike stable or transient transfection-based screening, which requires a minimum of 7 days for setup and execution, results using our CHO-based CFPS platform are attained within 2 days and it is well-suited for automation. Further development would provide a tool for rapid, high-throughput prediction of mAb expression ranking to accelerate design-build-test cycles required for antibody expression and engineering. Looking forward, the CHO-based CFPS platform could facilitate the synthesis of toxic proteins as well.