Biology subjects

Sun, S.

Publications and source records attributed to Sun, S..

At least 253 records · Page 14Linked to original sources

bioRxiv2022

Tumor landscape of epithelial ovarian cancer highlights that EGR1 drives tumor invasion at single-cell resolution

Identifying underlying molecular mechanisms and biomarkers of epithelial ovarian carcinoma (EOC) proliferation and metastasis remains challenging. Patients of EOC are usually diagnosed at an advanced stage and the availability of invasion-related targets is limited. Herein, we explored the single-cell RNA sequencing (scRNA-seq) dataset of EOC and defined tumor physiological reprograming compared to bulk RNA-seq. The energy metabolism and anti-apoptotic pathway was found as critical contributors to intratumor heterogeneity. Moreover, hypoxia, oxidative phosphorylation (OXPHOS) and glycolysis were positively correlated, which have biologically activity trajectories during epithelial mesenchymal transition (EMT). The HMGH1, EGR1 and RUNX1 were found to be critical inducers of the EMT process in EOC. Experimental validation revealed that suppressed EGR1 decreased the expression of FAS and HSPG2 and associating with EMT progression in EOC. In tumor microenvironment (TME), CAFs were found have significant contribution to tumor immune infiltration and metastasis and accumulation of CAFs was associated with poorer patient survival. In conclusion, physiological features and molecular mechanisms in the TME of EOC were revealed and provided effective targets for the suppression of tumor metastasis.

bioinformatics↗

bioRxiv2022

Heterogeneity of RNA editing in mesothelioma and how RNA editing enzyme ADAR2 affects mesothelioma cell growth, response to chemotherapy and tumor microenvironment

We previously observed increased levels of adenosine-deaminase-acting-on-dsRNA (Adar)-dependent RNA editing during mesothelioma development in mice exposed to asbestos. The aim of this study was to characterize and assess the role of ADAR-dependent RNA editing in mesothelioma. Tumors and mesothelioma primary cultures have higher ADAR-mediated RNA editing compared to mesothelial cells. Unsupervised clustering of editing in different genomic regions revealed heterogeneity between tumor samples as well as mesothelioma primary cultures. ADAR2 expression levels are higher in BRCA1-associated protein 1 wild-type tumors, with corresponding changes in RNA editing in transcripts and 3UTR. ADAR2 knockdown and rescue models indicated a role in cell proliferation, altered cell cycle, increased sensitivity to antifolate treatment and type-1 interferon signaling upregulation, leading to changes in the microenvironment in vivo. Our data indicate that RNA editing contributes to mesothelioma heterogeneity and highlights an important role of ADAR2 not only in growth regulation in mesothelioma but also chemotherapy response, in addition to regulating inflammatory response downstream of sensing nucleic acid structures.

cancer biology↗

bioRxiv2022

Accurate and efficient protein sequence designthrough learning concise local environment of residues

Protein sequence design has been widely applied in rational protein engineering and increasing the design accuracy and efficiency is highly desired. Here we present ProDESIGN-LE, an accurate and efficient design approach, which adopts a concise but informative representation of residues local environment and trains a transformer to select an appropriate residue at a position from its local environment. ProDESIGN-LE iteratively applies the transformer on the positions in the target structure, eventually acquiring a designed sequence with all residues fitting well with their local environments. ProDESIGN-LE designed sequences for 68 naturally occurring and 129 hallucinated proteins within 20 seconds per protein on average, and the predicted structures from the designed sequences perfectly resemble the target structures with state-of-the-art average TM-score exceeding 0.80. We further experimentally validated ProDESIGN-LE by designing five sequences for an enzyme, chloramphenicol O-acetyltransferase type III (CAT III), and recombinantly expressing the proteins in E. coli. Of these proteins, three exhibited excellent solubility, and one yielded monomeric species with circular dichroism spectra consistent with the natural CAT III protein.

bioinformatics↗

bioRxiv2022

Predicting the antigenic evolution of SARS-COV-2 with deep learning

The severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) antigenic profile evolves in response to the vaccine and natural infection-derived immune pressure, resulting in immune escape and threatening public health. Exploring the possible antigenic evolutionary potentials improves public health preparedness, but it is limited by the lack of experimental assays as the sequence space is exponentially large. Here we introduce the Machine Learning-guided Antigenic Evolution Prediction (MLAEP), which combines structure modeling, multi-task learning, and genetic algorithm to model the viral fitness landscape and explore the antigenic evolution via in silico directed evolution. As demonstrated by existing SARS-COV-2 variants, MLAEP can infer the order of variants along antigenic evolutionary trajectories, which is also strongly correlated with their sampling time. The novel mutations predicted by MLAEP are also found in immunocompromised covid patients and newly emerging variants, like XBB1.5. The predictions of MLAEP were validated by conducting in vitro neutralizing antibody binding assay, which demonstrated that the model-generated variants displayed significantly increased immune evasion ability compared with the controls. In sum, our approach enables profiling existing variants and forecasting prospective antigenic variants, thus may help guide the development of vaccines and increase preparedness against future variants. Our model is available at https://mlaep.cbrc.kaust.edu.sa.

evolutionary biology↗

bioRxiv2022

Synaptic homeostasis transiently leverages Hebbian mechanisms for a multiphasic response to inactivity

Neurons use various forms of negative feedback to maintain their synaptic strengths within an operationally useful range. While this homeostatic plasticity is thought to distinctly counteract the destabilizing positive feedback of Hebbian plasticity, there is considerable overlap in the molecular components mediating both forms of plasticity. The varying kinetics of these components spurs additional inquiry into the dynamics of synaptic homeostasis. We discovered that upscaling of synaptic weights in response to prolonged inactivity is nonmonotonic. Surprisingly, this seemingly oscillatory adaptation involved transient appropriation of molecular effectors associated with Hebbian plasticity, namely CaMKII, L-type Ca2+ channels, and Ca2+-permeable AMPARs, and homeostatic elements such as calcineurin. We created a dynamic model that shows how traditionally "Hebbian" and "homeostatic" mechanisms can cooperate to autoregulate postsynaptic Ca2+ levels. We propose that this combination of mechanisms allows excitatory synapses to adapt to prolonged activity changes and safeguard the capability to undergo future strengthening on demand.

neuroscience↗

bioRxiv2022

Respiratory mucosal vaccination of peptide-poloxamine-DNA nanoparticles provides complete protection against lethal SARS-CoV-2 challenge

The ongoing SARS-CoV-2 pandemic represents a brutal reminder of the continual threat of mucosal infectious diseases. Mucosal immunity may provide robust protection at the predominant sites of SARS-CoV-2 infection. However, it remains unclear whether respiratory mucosal administration of DNA vaccines could confer protective immune responses against SARS-CoV-2 challenge due to the insurmountable barriers posed by the airway. Here, we applied self-assembled peptide-poloxamine nanoparticles with mucus-penetrating properties for pulmonary inoculation of a COVID-19 DNA vaccine (pSpike/PP-sNp). Not only displays the pSpike/PP-sNp superior gene-transfection and favorable biocompatibility in the mouse airway, but pSpike/PP-sNp promotes a tripartite immunity consisting of systemic, cellular and mucosal immune responses that are characterized by mucosal IgA secretion, high levels of neutralizing antibodies, and resident memory phenotype T-cell responses in the lungs of mice. Most importantly, pSpike/PP-sNp completely eliminates SARS-CoV-2 infection in both upper and lower respiratory tracts and enables 100% survival rate of mice following lethal SARS-CoV-2 challenge. Our findings indicate PP-sNp might be a promising platform in mediating DNA vaccines to elicit all-around mucosal immunity against SARS-CoV-2.

immunology↗

bioRxiv2022

Microfluidic chemostatic bioreactor for high-throughput screening and sustainable co-harvesting of biomass and biodiesel in microalgae

As a renewable and sustainable source for energy, environment, and biomedical applications, microalgae and microalgal biodiesel have attracted great attention. However, their applications are confined due to the cost-efficiency of microalgal mass production. One-step strategy and continuous culturing systems could be solutions. However, current studies for optimization throughout microalgae-based biofuel production pipelines are generally derived from the batch culture process. Better tools are needed to study algal growth kinetics in continuous systems. A microfluidics chemostatic bioreactor array was presented, providing low-adhesion cultivation for algae in the gas, nutrition, and temperature (GNT) well-controlled environment with high throughput. The chip wasused to mimic the continuous culture environment of bioreactors. It allowed simultaneously studying of 8x8 different chemostatic conditions on algal growth and oil production in parallel on a 7x7 cm2 footprint. On-chip experiments of batch and continuous cultures of Chlorella. sp. were performed to study growth and lipid accumulation under different nitrogen concentrations. The results demonstrated that microalgal cultures can be regulated to grow and accumulate lipids concurrently, thus enhancing lipid productivity in one step. The developed on-chip culturing condition screening, which was more suitable for continuous bioreactor, was achieved at a half shorter time, 64-times higher throughput, and less reagent consumption. It could be used to establish chemostat cultures in continuous bioreactors which can dramatically accelerate the development of renewable and sustainable algal for CO2 fixation and biosynthesis and related systems for advanced sustainable energy, food, pharmacy, and agriculture with enormous social and ecological benefits. TEASERSustainable microfluidic bioreactor for 64 times higher-throughput screening CO2 fixation and biomass and biodiesel production in microalgae.

bioengineering↗

bioRxiv2022

Tbx2 is essential for cochlear inner hair cell development and regeneration

Atoh1 is essential for the development of outer hair cells (OHCs) and inner hair cells (IHCs) in the mammalian cochlea. Whereas Ikzf2 is necessary for OHC development, the key gene for IHC development remains unknown. We found that deleting Tbx2 in neonatal IHCs led to their trans-differentiation into OHCs, by repressing 26.7% of IHC and inducing 56.3% of OHC genes, including Ikzf2. More importantly, persistent expression of Tbx2 together with transient Atoh1 effectively reprogramed non-sensory supporting cells into new IHCs expressing functional IHC marker vGlut3. The differentiation status of these new IHCs is much more advanced than those previously reported. Thus, Tbx2 is essential for IHC development, and its co-upregulation with Atoh1 in supporting cells represents a new approach for treating IHC degeneration-related deafness.

developmental biology↗

bioRxiv2022

satmut_utils: a simulation and variant calling package for multiplexed assays of variant effect

BackgroundThe impact of thousands of individual genetic variants on molecular phenotypes for disease-relevant genes remains unknown. Multiplexed assays for variant effect (MAVEs) are highly scalable methods to annotate the relevant variants. However, current software methods for analyzing MAVEs lack standardized annotation, can require cumbersome configuration, and do not easily scale to large target regions. ResultsHere, we present satmut_utils as a flexible solution for 1) simulation of saturation mutagenesis data; and 2) quantification of variants across four orders of magnitude from multiplexed assay data. Improvements of satmut_utils over existing solutions include support for multiple experimental strategies, unique molecular identifier-based consensus deduplication, and machine learning-based error correction. We developed a rigorous simulation workflow to validate the performance of satmut_utils and carried out the first benchmarking of existing software for variant calling. Finally, we used satmut_utils to determine the mRNA abundance of thousands of coding variants in cystathionine beta-synthase (CBS) by two library preparation methods. We identified an association between variants near chemical cofactor binding sites and decreased mRNA abundance. We also found a correlation between codon optimality and the magnitude of variant effects, emphasizing the potential of single-nucleotide variants to alter mRNA abundance. Conclusionssatmut_utils enables high-performance analysis of saturation mutagenesis data, achieves unprecedented specificity through novel error correction approaches, and reveals the capability of single-codon variants to alter mRNA abundance in native coding sequences.

genomics↗

bioRxiv2022

Identification of two bZIP transcription factors that regulate development of pavement and trichome cells in Arabidopsis thaliana by single-cell RNA-sequencing

Epidermal cells are the main avenue for signal and material exchange between plants and the environment. Leaf epidermal cells primarily include pavement cells (PCs), guard cells, and trichomes cells (TCs), which differentiate from protodermal cells or meristemoids. The development and distribution of different epidermal cells are tightly regulated by a complex transcriptional regulatory network mediated by phytohormones, including jasmonic acid (JA), and transcription factors. Understanding how the fate of leaf epidermal cells is determined, however, is still largely unknown due to the diversity of cell types and the complexity of its regulation. Here, we characterized the transcriptional profiles of epidermal cells in 3-day-old true leaves of Arabidopsis thaliana using single-cell RNA-sequencing. We identified two genes encoding BASIC LEUCINE-ZIPPER (bZIP) transcription factors, namely the bZIP25 and bZIP53, which are highly expressed in PCs and early-stage meristemoid cells. Densities of PCs and TCs were found to increase and decrease, respectively, in bzip25 and bzip53 mutants, compared with wild-type plants. This trend was more pronounced in the presence of JA, suggesting that these transcription factors regulate the development of TCs and PCs in response to JA. IN A NUTSHELLO_ST_ABSBackgroundC_ST_ABSLeaf epidermal cells, comprised of trichome cells (TCs), guard cells (GCs), and pavement cells (PCs), are responsible for exchanging materials and information between plants and the surrounding aerial environment. Many genes have been identified in Arabidopsis thaliana and confirmed to be involved in the initiation and differentiation of TCs and PCs. The fate determination of TCs and PCs is tightly regulated by positive and negative regulators at the cellular level. The precise underlying molecular mechanisms responsible for the fate determination of TCs and PCs, however, are still unclear at this time. QuestionWhat are the transcriptomic profiles of different leaf epidermal cell types? Can we dissect the genes that are specifically expressed in certain epidermal cell types? What kinds of transcription factors are involved in regulating the fate determination of TCs and PCs? FindingsWe performed single cell RNA-seq to investigate the transcriptomic profiles of different leaf epidermal cell types and identified differentially expressed genes in each cell type. We found that genes that are involved in jasmonic acid signaling are highly expressed in early-stage meristemoid (EM) cells which can act as the precursor of PCs and perhaps of TCs. To investigate the regulatory mechanisms underlying EM development, we identified the transcription factors (TFs) in EM cells and found that two bZIP TF genes, bZIP25 and bZIP53, are highly expressed in EMs. Further analyses of these two genes using both loss-of-function and gain-of-function approaches indicated that bZIP25 and bZIP53 are functionally involved in promoting trichome formation but inhibit pavement cell development in response to jasmonic acid. Next stepsBesides of bZIP25 and bZIP53, we also identified other key genes, for example FES1B, in leaf epidermal cells. Our next step will be to explore the regulation of other key genes involved in the fate determination of different cell types in leaf epidermis.

plant biology↗

bioRxiv2022

Systematic classification error profoundly impacts inference in high-depth Whole Genome Shotgun Sequencing datasets

There is little consensus in the literature as to which approach for classification of Whole Genome Shotgun (WGS) sequences is best. In this paper, we examine two of the most popular algorithms, Kraken2 and Metaphlan2 utilizing four publicly available datasets. As expected from previous literature, we found that Kraken2 reports more overall taxa while Metaphlan2 reports fewer taxa while classifying fewer overall reads. To our surprise, however, Kraken 2 reported not only more taxa but many more taxa that were significantly associated with metadata. This implies that either Kraken2 is more sensitive to taxa that are biologically relevant and are simply missed by Metaphlan2, or that Kraken2s classification errors are generated in such a way to impact inference. To discriminate between these two possibilities, we compared Spearman correlations coefficients of each taxa against each taxa with higher abundance from the same dataset. We found that Kraken2, but not Metaphlan2, showed a consistent pattern of classifying low abundance taxa that generated high correlation coefficients with higher abundance taxa. Neither Metaphlan2, nor 16S sequences that were available for two of our four datasets, showed this pattern. Simple simulations based on a variable Poisson error rate sampled from the uniform distribution with an average error rate of 0.0005 showed strikingly strong concordance with the observed correlation patterns from Kraken2. Our results suggest that Kraken2 consistently misclassifies high abundance taxa into the same erroneous low abundance taxa creating "phantom" taxa have a similar pattern of inference as the high abundance source. Because of the large sequencing depths of modern WGS cohorts, these "phantom" taxa will appear statistically significant in statistical models even with a low overall rate of classification error from Kraken. Our simulations suggest that this can occur with average error rates as low as 1 in 2,000 reads. These data suggest a novel metric for evaluating classifier accuracy and suggest that the pattern of classification errors should be considered in addition to overall classification error rate since consistent classification errors have a more profound impact on inference compared to classification errors that do not always result in assignment to the same erroneous taxa. This work highlights fundamental questions on how classifiers function and interact with large sequencing depth and statistical models that still need to be resolved for WGS, especially if correlation coefficients between taxa are to be used to build covariance networks. Our work also suggests that despite its limitations, 16S rRNA sequencing may still be useful as neither of the two most popular 16S classifiers showed these patterns of inflated correlation coefficients between taxa.

bioinformatics↗

bioRxiv2022

Obligate sexual reproduction of a homothallic fungus closely related to the Cryptococcus pathogenic species complex

Sexual reproduction is a ubiquitous and ancient trait of eukaryotic life. While sexual organisms are usually faced with the challenge of finding a compatible mating partner, species as diverse as animals, plants, and fungi have repeatedly evolved the ability to reproduce sexually without an obligate requirement for another individual. Here, we uncovered the underlying mechanism of self-compatibility (homothallism) in Cryptococcus depauperatus, a fungal species sister to the clinically relevant human fungal pathogens Cryptococcus neoformans and Cryptococcus gattii species complexes. In contrast to C. neoformans or C. gattii, which grow as a yeast in the asexual stage, and produce hyphae, basidia, and infectious spores during the sexual stage, C. depauperatus grows exclusively as hyphae decorated with basidia and abundant spores and appears to be continuously engaged in sexual reproduction. By combining the insights from comparative genomics and genetic analyses of mutants defective in key mating and meiosis genes, we demonstrate the sexual cycle of C. depauperatus involves meiosis, and reveal that self-compatibility is orchestrated by the expression, in the same cell, of an unlinked mating receptor (Ste3a) and pheromone ligand (MF) pair seemingly derived from opposite mating types of a heterothallic (self-sterile) ancestor. We identified a putative mating-type (MAT) determining region containing genes phylogenetically aligned with MATa alleles of other species, and a few MAT gene alleles scattered and unlinked throughout the genome, but no homologs of the mating-type homeodomain genes SXI1 (HD1) and SXI2 (HD2). Comparative genomic analyses suggested a dramatic remodeling of the MAT locus possibly owing to reduced selective constraints to maintain mating-type genes in tight linkage, associated with a transition to self-fertility. Our findings support C. depauperatus as an obligately sexual, homothallic fungal species and provide additional insight into the repeated transitions between modes of sexual reproduction that have occurred throughout the fungal kingdom.

microbiology↗

bioRxiv2022

An integrative analysis of the biological clock hypothesis in human gut microbiome

BackgroundWhile previous studies have explored the relationship between aging and the gut microbiome, it remains unclear how consistent and reproducible this association is across different cultures and groups. We performed an integrative analysis with 11 independent datasets from nine different countries to test the idea that the aging gut microbiome can be viewed as a biological clock, in which microbial changes associated with age are consistent and measurable across distinct datasets. ResultsAs expected, our Principal Coordinate Analysis found strong batch effects with study ID by far the strongest signal across datasets. Despite this large batch effect, we found a consistent signal across studies that was largely driven by sample size with only our larger cohorts showing taxa in common associated with age. Likewise, Shannon diversity and richness were not consistently associated with age across the 11 datasets, but some positive correlations with richness and host age were observed among the four largest cohorts. The taxon with the most potential as a biomarker for the aging human gut microbiome is genus Bifidobacterium, with significantly negative associations with host age in three out of the four datasets that had more than 200 samples. ConclusionThe driving force behind low reproducibility of association of age with the microbiome in previous studies appears to be inadequate sample size rather than structural differences in the microbial community based on cohort characteristics. Results from a power analysis suggest that future studies on the aging human gut microbiome consider on the order of 100-300 samples to consistently observe an age signal. With these larger sample sizes, parametric and non-parametric model yield broadly similar power.

bioinformatics↗

bioRxiv2022

SRSF10 is essential for progenitor spermatogonia expansion by regulating alternative splicing

Alternative splicing expands the transcriptome and proteome complexity and plays essential roles in tissue development and human diseases. However, how alternative splicing regulates spermatogenesis remains largely unknown. Here, using germ cell-specific knockout mouse model, we demonstrated that the splicing factor Srsf10 is essential for spermatogenesis and male fertility. Depletion of Srsf10 in germ cells had little effect on the formation of SSCs but impeded the expansion of progenitor spermatogonia, leading to the failure of spermatogonia differentiation and meiosis initiation. This was further evidenced by the decreased expression of progenitor cell markers in bulk RNA-seq, and much less progenitor and differentiating spermatogonia in single-cell RNA-seq data. Furthermore, the expression of genes involved in cell cycle was abnormal in all subtypes of spermatogonia identified in single-cell RNA-seq data. Notably, using isolated spermatogonia, we found that Srsf10 depletion disturbed the alternative splicing of hundreds of genes, which were preferentially associated with cell cycle, mitotic cell cycle checkpoint and germ cell development, including Dazl, Kit, Ret, Sycp1, Nasp and Bora. These data suggest that SRSF10 is critical for the expansion of progenitor spermatogonia by regulating alternative splicing, expanding our understanding of the mechanism underlying spermatogenesis.

developmental biology↗

bioRxiv2022

Profiling Genetic Diversity Reveals the Molecular Basis for Balancing Function with Misfolding in Alpha-1 Antitrypsin

Genetic variation of alpha-1 antitrypsin (AAT) is responsible for alpha-1-antitrypsin deficiency (AATD) leading to gain-of-toxic aggregation in the liver and loss-of-function on neutrophil elastase (NE) inhibitory activity in the lung contributing to chronic obstructive pulmonary disease (COPD) during aging. To probe the molecular basis for how biology designs the protein fold to achieve balance between sequence, function and structure contributing to AATD in the population, we measured the intracellular monomer and polymer, secreted monomer and polymer and NE inhibitory activity of 75 alpha-1-antitrypsin (AAT) variants. To address the complex folding dynamics affecting the form and function of the protein fold that is differentially impacted by variants in the population, we applied a Gaussian process regression (GPR) based machine learning approach termed variation spatial profiling (VSP). By using a sparse collection of extant variants to link genotype to phenotype, VSP maps spatial covariance (SCV) relationships that quantitate the functional value of every residue in the wild-type (WT) AAT sequence with defined uncertainty in the context of its protein fold design. The SCV-based uncertainty allows us to pinpoint critical short- and long-range residue interactions involving 3 regions-the N-terminal (N1), middle (M2) and carboxyl-terminal (C3) of AAT polypeptide sequence that differentially contribute to the balance between function and misfolding of AAT, thus providing an unanticipated platform for precision therapeutic development for liver and lung disease. By understanding mechanistically the complex fold design of the metastable WT AAT fold, we posit that GPR-based SCV provides a foundation for understanding the evolutionary design of the fold from the ensemble of structures found in the population driving biology for precision management of AATD in the individual.

molecular biology↗

bioRxiv2022

Highly efficient generation of blastocyst-like structures from mouse totipotent blastomere-like cells

Mammalian embryogenesis begins with a totipotent zygote. Early embryogenesis can be recapitulated by aggregated extended pluripotent stem cells (EPSCs) in a 3D culture system. However, the efficiency of generating blastoids is low and whether other reported totipotent stem cells retained a similar capacity remains unknown. Here we show that spliceosomal repressed totipotent blastomere-like cells (TBLCs) form blastocyst-like structures when aggregated in 3D microwells with around 80% efficiency. TBLC-blastoids resemble blastocyst in morphology and cell-lineage allocation, show similar transcriptional profile with natural blastocyst and contain more TE cells and fewer undefined intermediate cells compared to blastoids from EPSCs. Moreover, TBLC-blastoids can develop beyond the implantation stage in vitro and induce decidualization after transferred into uterus. In summary, we supply an alternative cell type to generate ameliorated blastoids highly efficiently for studying early mouse embryogenesis.

developmental biology↗

bioRxiv2022

Cell-specific regulation of gene expression using splicing-dependent frameshifting.

Precise and reliable cell-specific gene delivery remains technically challenging. Here we report a splicing-based approach for controlling gene expression whereby separate translational reading frames are coupled to the inclusion or exclusion of cell-specific alternative exons. Candidate exons are identified by analyzing thousands of publicly available RNA sequencing datasets and filtering by cell specificity, sequence conservation, and local intron length. This method, which we denote splicing-linked expression design (SLED), can be combined in a Boolean manner with existing techniques such as minipromoters and viral capsids. SLED vectors can leverage the strong expression of constitutive promoters, without sacrificing precision, by decoupling the tradeoff between promoter strength and selectivity. We generated SLED vectors to selectively target all neurons, photoreceptors, or excitatory neurons, and demonstrated that specificity was retained in vivo when delivered using AAVs. We further demonstrated the utility of SLED by creating what would otherwise be unobtainable research tools, specifically a GluA2 flip/flop reporter and a dual excitatory/inhibitory neuronal calcium indicator. Finally, we show the translational potential of SLED by rescuing photoreceptor degeneration in Prph2rds/rds mice and by developing an oncolytic vector that can selectively induce apoptosis in SF3B1 mutant cancer cells. The flexibility of SLED technology enables new avenues for basic and translational research.

molecular biology↗

bioRxiv2022

Closely related type II-C Cas9 orthologs recognize diverse PAMs

Autosomal dominant diseases can be treated by allele-specific disruption of mutant alleles. If the missense mutation generates a novel protospacer-adjacent motif (PAM), CRISPR-Cas9 can distinguish mutant alleles from wild-type alleles by a PAM-specific approach. Therefore, it is crucial to develop a CRISPR toolbox capable of recognizing multiple PAMs. Here, by using a GFP-activation assay, we tested the activities of 29 type II-C orthologs closely related to Nme1Cas9, 25 of which are active in human cells. These orthologs recognize diverse PAMs with variable length and nucleotide preference, including purine-rich, pyrimidine-rich, and mixed purine and pyrimidine PAMs. We characterized in depth the activity and specificity of Nsp2Cas9. We also generated a chimeric Cas9 nuclease that recognizes a simple N4C PAM, representing the most relaxed PAM preference for compact Cas9s to date. These Cas9 nucleases significantly enhance our ability to perform allele-specific genome editing.

genetics↗