Biology subjects

Zhao, H.

Publications and source records attributed to Zhao, H..

At least 541 records · Page 30Linked to original sources

bioRxiv2019

Sirolimus plus nintedanib treats vascular pathology in HHT mouse models

Hereditary hemorrhagic telangiectasia (HHT), a genetic bleeding disorder leading to systemic arteriovenous malformations (AVMs), is caused by loss-of-function mutations in the ALK1-ENG-Smad1/5/8 pathway. Evidence suggests that HHT pathogenesis strongly relies on overactivated PI3K-Akt-mTOR and VEGFR2 pathways in endothelial cells (ECs). In the BMP9/10-immunoblocked (BMP9/10ib) neonatal mouse model of HHT, we report here that the mTOR inhibitor, sirolimus, and the receptor tyrosine-kinase inhibitor, nintedanib, could synergistically fully block, but also reversed, retinal AVMs to avert retinal bleeding and anemia. Sirolimus plus nintedanib prevented vascular pathology in the oral mucosa, lungs, and liver of the BMP9/10ib mice, as well as significantly reduced gastrointestinal bleeding and anemia in inducible ALK1-deficient adult mice. Mechanistically, in vivo in BMP9/10ib mouse ECs, sirolimus and nintedanib blocked the overactivation of mTOR and VEGFR2, respectively. Furthermore, we found that sirolimus activated ALK2-mediated Smad1/5/8 signaling in primary ECs--including in HHT patient blood outgrowth ECs--and partially rescued Smad1/5/8 activity in vivo in BMP9/10ib mouse ECs. These data demonstrate that the combined correction of endothelial Smad1/5/8, mTOR, and VEGFR2 pathways opposes HHT pathogenesis. Repurposing of sirolimus plus nintedanib might provide therapeutic benefit in HHT patients.

cell biology↗

bioRxiv2019

Shotgun Metagenomics of 361 elderly women reveals gut microbiome change in bone mass loss

Bone mass loss contributes to the risk of bone fracture in the elderly. Many factors including age, obesity, estrogen and diet, are associated with bone mass loss. Mice studies suggest that the intestinal microbiome might influence the bone mass by regulating the immune system, however there has been little evidence from human studies. We have recruited 361 Chinese elderly women to collect data for a metagenomic-wide association study (MWAS) to investigate the influence of the gut microbiome on bone health. Gut microbiome data were produced using BGISEQ500 sequencing, BMD was calculated using Hologic dual energy X-ray machine, BMI (Body Mass Index) and age were also provided. This therefore data allows exploration of gut microbiome diversity and links to bone mass loss, as well as microbial species and modules as markers for bone mineral density. Making these data potentially useful in studying the role the gut microbiota might play in bone mass loss and offering exploration into the bone mass loss process.

microbiology↗

bioRxiv2019

Mutations of the YidC Insertase alleviate stress from σM-dependent membrane protein overproduction in Bacillus subtilis

In Bacillus subtilis, the extracytoplasmic function {sigma} factor {sigma}M regulates cell wall synthesis and is critical for intrinsic resistance to cell wall targeting antibiotics. The anti-{sigma} factors YhdL and YhdK form a complex that restricts the basal activity of {sigma}M, and the absence of YhdL leads to runaway expression of the {sigma}M regulon and cell death. Here, we report that this lethality can be suppressed by gain-of-function mutations in spoIIIJ, which encodes the major YidC membrane protein insertase in B. subtilis. B. subtilis PY79 SpoIIIJ contains a single amino acid substitution in the substrate-binding channel (Q140K), and this allele suppresses the lethality of high SigM. Analysis of a library of YidC variants reveals that increased charge (+2 or +3) in the substrate-binding channel can compensate for high expression of the {sigma}M regulon. Derepression of the {sigma}M regulon induces secretion stress, oxidative stress and DNA damage responses, all of which can be alleviated by the YidCQ140K substitution. We further show that the fitness defect caused by high {sigma}M activity is exacerbated in the absence of SecDF protein translocase or {sigma}M-dependent induction of the Spx oxidative stress regulon. Conversely, cell growth is improved by mutation of specific {sigma}M-dependent promoters controlling operons encoding integral membrane proteins. Collectively, these results reveal how the {sigma}M regulon has evolved to up-regulate membrane-localized complexes involved in cell wall synthesis, and to simultaneously counter the resulting stresses imposed by regulon induction.\n\nAuthor SummaryBacteria frequently produce antibiotics that inhibit the growth of competitors, and many naturally occurring antibiotics target cell wall synthesis. In Bacillus subtilis, the alternative {sigma} factor {sigma}M is induced by cell wall antibiotics, and upregulates genes for peptidoglycan and cell envelope synthesis. However, dysregulation of the {sigma}M regulon, resulting from loss of the YhdL anti-{sigma}M protein, is lethal. We here identify charge variants of the SpoIIIJ(YidC) membrane protein insertase that suppress the lethal effects of high {sigma}M activity. Further analyses reveal that induction of the {sigma}M regulon leads to high level expression of membrane proteins that trigger envelope stress, and this stress is countered by specific genes in the {sigma}M regulon.

microbiology↗

bioRxiv2019

Identifying Combinations of Cancer Drivers in Individual Patients.

Identifying the subset of genetic alterations present in individual tumors that are essential and collectively sufficient for cancer initiation and progression would advance the development of effective personalized treatments. We present CRSO for inferring the combinations of alterations, i.e., rules, that cooperate to drive tumor formation in individual patients. CRSO prioritizes rules by integrating patient-specific passenger probabilities for individual alterations along with information about the recurrence of particular combinations throughout the population. We present examples in glioma, liver cancer and melanoma of significant differences in patient outcomes based on rule assignments that are not identifiable by consideration of individual alterations.

bioinformatics↗

bioRxiv2019

DNA Punch Cards: Encoding Data on Native DNA Sequences via Topological Modifications

Synthetic DNA-based data storage systems have received significant attention due to the promise of ultrahigh storage density and long-term stability. However, all platforms proposed so far suffer from high cost, read-write latency and error-rates that render them noncompetitive with modern optical and magnetic storage devices. One means to avoid synthesizing DNA and to reduce the system error-rates is to use readily available native DNA. As the symbol/nucleotide content of native DNA is fixed, one may adopt an alternative recording strategy that modifies the DNA topology to encode desired information. Here, we report the first macromolecular storage paradigm in which data is written in the form of "nicks (punches)" at predetermined positions on the sugar-phosphate backbone of native dsDNA. The platform accommodates parallel nicking on multiple "orthogonal" genomic DNA fragments and paired nicking and disassociation for creating "toehold" regions that enable single-bit random access and strand displacement in-memory computations. As a proof of concept, we used the programmable restriction enzyme Pyrococcus furiosus Argonaute to punch two files into the PCR products of Escherichia coli genomic DNA. The encoded data is accurately reconstructed through high-throughput sequencing and read alignment.

synthetic biology↗

bioRxiv2019

Arabidopsis Proteome and the Mass Spectral Assay Library

Arabidopsis is an important model organism and the first plant with its genome sequenced. Knowledge from studying this species has either direct or indirect applications to agriculture and human health. Quantitative proteomics by data-independent acquisition (SWATH/DIA-MS) was recently developed and considered as a high-throughput targetedlike approach for accurate proteome quantitation. In this approach, a high-quality and comprehensive library is a prerequisite. Here, we generated a protein expression atlas of 10 organs of Arabidopsis and created a library consisting of 15,514 protein groups, 187,265 unique peptide sequences, and 278,278 precursors. The identified protein groups correspond to ~56.5% of the predicted proteome. Further proteogenomics analysis identified 28 novel proteins. We subsequently applied DIA-mass spectrometry using this library to quantify the effect of abscisic acid on Arabidopsis. We were able to recover 8,793 protein groups with 1,787 of them being differentially expressed which includes 65 proteins known to respond to abscisic acid stress. Mass spectrometry data are available via ProteomeXchange with identifier PXD012710 for data-dependent acquisition and PXD014032 for DIA analyses.\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@1a3f799org.highwire.dtl.DTLVardef@1d4711dorg.highwire.dtl.DTLVardef@4e3f73org.highwire.dtl.DTLVardef@127a9a4org.highwire.dtl.DTLVardef@f254bb_HPS_FORMAT_FIGEXP M_TBL C_TBL

plant biology↗

bioRxiv2019

Retrospective Association Analysis of Longitudinal Binary Traits Identifies Important Loci and Pathways in Cocaine Use

Longitudinal phenotypes have been increasingly available in genome-wide association studies (GWAS) and electronic health record-based studies for identification of genetic variants that influence complex traits over time. For longitudinal binary data, there remain significant challenges in gene mapping, including misspecification of the model for the phenotype distribution due to ascertainment. Here, we propose L-BRAT, a retrospective, generalized estimating equations-based method for genetic association analysis of longitudinal binary outcomes. We also develop RGMMAT, a retrospective, generalized linear mixed model-based association test. Both tests are retrospective score approaches in which genotypes are treated as random conditional on phenotype and covariates. They allow both static and time-varying covariates to be included in the analysis. Through simulations, we illustrated that retrospective association tests are robust to ascertainment and other types of phenotype model misspecification, and gain power over previous association methods. We applied L-BRAT and RGMMAT to a genome-wide association analysis of repeated measures of cocaine use in a longitudinal cohort. Pathway analysis implicated association with opioid signaling and axonal guidance signaling pathways. Lastly, we replicated important pathways in an independent cocaine dependence case-control GWAS. Our results illustrate that L-BRAT is able to detect important loci and pathways in a genome scan and to provide insights into genetic architecture of cocaine use.

genetics↗

bioRxiv2019

To Improve Protein Sequence Profile Prediction through Image Captioning on Pairwise Residue Distance Map

Protein sequence profile prediction aims to generate multiple sequences from structural information to advance the protein design. Protein sequence profile can be computationally predicted by energy-based method or fragment-based methods. By integrating these methods with neural networks, our previous method, SPIN2 has achieved a sequence recovery rate of 34%. However, SPIN2 employed only one dimensional (1D) structural properties that are not sufficient to represent 3D structures. In this study, we represented 3D structures by 2D maps of pairwise residue distances. and developed a new method (SPROF) to predict protein sequence profile based on an image captioning learning frame. To our best knowledge, this is the first method to employ 2D distance map for predicting protein properties. SPROF achieved 39.8% in sequence recovery of residues on the independent test set, representing a 5.2% improvement over SPIN2. We also found the sequence recovery increased with the number of their neighbored residues in 3D structural space, indicating that our method can effectively learn long range information from the 2D distance map. Thus, such network architecture using 2D distance map is expected to be useful for other 3D structure-based applications, such as binding site prediction, protein function prediction, and protein interaction prediction.

bioinformatics↗

bioRxiv2019

An antisense oligonucleotide leads to suppressed transcriptional elongation of Hdac2 and long-term memory enhancement

Repression of the memory suppressor gene histone deacetylase 2 (Hdac2) in mice elicits cognitive enhancement, and drugs that block HDAC2 catalytic activity are being investigated for treating disorders affecting memory. Currently available compounds that target HDAC2 are not specific to the HDAC2 isoform, and have short half-lives. Antisense oligonucleotides (ASOs) are a class of drugs that base pair with RNA targets and exhibit extremely long-lasting, specific inhibition relative to small molecule drugs. We utilized an ASO to reduce Hdac2 messenger RNA (mRNA) quantities, and explored its longevity, specificity, and mechanism of repression. A single injection of the Hdac2-targeted ASO in the central nervous system diminished Hdac2 mRNA levels for at least 4 months in the brain, and knockdown of this factor resulted in significant memory enhancement for 8 weeks in mice. RNA-seq analysis of brain tissues revealed that the ASO repression was specific to the Hdac2 isoform relative to other classical Hdac genes, and caused alterations in levels of other memory-associated mRNAs. In cultured neurons, we observed that the Hdac2-targeted ASO suppressed Hdac2 mRNA and an Hdac2 non-coding regulatory extra-coding RNA (ecRNA). The ASO not only triggered a reduction in mRNA levels, but also elicited direct transcriptional suppression of the Hdac2 gene through blocking RNA polymerase II elongation. These findings suggest transcriptional suppression of the target gene as a novel mechanism of action of ASOs, and opens up the possibility of using ASOs to achieve lasting gene silencing in the brain without altering the nucleotide sequence of a gene.

pharmacology and toxicology↗

bioRxiv2019

Accurate Prediction of Genome-wide RNA Secondary Structure Profile Based On Extreme Gradient Boosting

MotivationMany studies have shown that RNA secondary structure plays a vital role in fundamental cellular processes, such as protein synthesis, mRNA processing, mRNA assembly, ribosome function and eukaryotic spliceosomes. Identification of RNA secondary structure is a key step to understand the common mechanisms underlying the translation process. Recently, a few experimental methods were developed to measure genome-wide RNA secondary structure profile through high-throughput sequencing techniques, and have been successfully applied to genomes including yeast and human. However, these high-throughput methods usually have low precision and are hard to cover all nucleotides on the RNA due to limited sequencing coverage.\n\nResultsIn this study, we developed a new method for the prediction of genome-wide RNA secondary structure profile (TH-GRASP) from RNA sequence based on eXtreme Gradient Boosting (XGBoost). The method achieves an prediction with areas under the receiver operating characteristic curve (AUC) values greater than 0.9 on three different datasets, and AUC of 0.892 by an independent test on the recently released Zika virus RNA dataset. These AUCs represent a consistent increase of >6% than the recently developed method CROSS trained by a shallow neural network. A further analysis on the 1000-Genome Project data showed that our predicted unpaired probability at mutations sites are highly correlated with the minor allele frequencies (MAF) of synonymous, non-synonymous mutations, and mutations in 3 and 5UTR with Pearson Correlation Coefficients all above 0.8. These PCCs are consistently higher than those generated by RNAplfold method. Moreover, an investigation over all human mRNA indicated a periodic distribution of the predicted unpaired probability on codons, and a decrease of paired probability in the boundary with 5 and 3 untranslated regions. These results highlighted TH-GRASP is effective to remove experimental noises and to have ability to make predictions on nucleotides with low or no coverage by fitting high-throughput genomic data for RNA secondary structure profiles, and also suggested that building model on high throughput experimental data might be a future direction to substitute analytical methods.\n\nAvailabilityThe TH-GRASP is available for academic use at https://github.com/sysu-yanglab/TH-GRASP.\n\nSupplementary informationSupplementary data are available online.

bioinformatics↗

bioRxiv2019

Light-sheet microscopy with isotropic, sub-micron resolution and solvent-independent large-scale imaging

We present cleared tissue Axially Swept Light-Sheet Microscopy (ctASLM), which achieves sub-micron isotropic resolution, high optical sectioning capability, and large field of view imaging (870x870 m2) over a broad range of immersion media. ctASLM can image live, expanded, and both aqueous and organic chemically cleared tissue preparations and provides 2- to 5-fold better axial resolution than confocal or other reported cleared tissue light-sheet microscopes. We image millimeter-sized tissues with sub-micron 3D resolution, which enabled us to perform automated detection of cells and subcellular features such as dendritic spines.

bioengineering↗

bioRxiv2019

Identification of a basal stem cell subpopulation in the prostate via functional, lineage tracing and single-cell RNA-seq analyses

The basal cell compartment in many epithelial tissues such as the prostate, bladder, and mammary gland are generally believed to serve as an important pool of stem cells. However, basal cells are heterogenous and the stem cell subpopulation within basal cells is not well elucidated. Here we uncover that the core epithelial-to-mesenchymal transition (EMT) inducer Zeb is exclusively expressed in a prostate basal cell subpopulation based on both immunocytochemical and cell lineage tracing analysis. The Zeb1+ prostate epithelial cells are multipotent prostate basal stem cells (PBSCs) that can self-renew and generate functional prostatic glandular structures with all three epithelial cell types at the single-cell level. Genetic ablation studies reveal an indispensable role for Zeb1 in prostate basal cell development. Utilizing unbiased single cell transcriptomic analysis of over 9000 mouse prostate basal cells, we find that Zeb1+ basal cell subset shares gene expression signatures with both epithelial and mesenchymal cells and stands out uniquely among all the basal cell clusters. Moreover, Zeb1+ epithelial cells can be detected in mouse and clinical samples of prostate tumors. Identification of the PBSC and its transcriptome profile is crucial to advance our understanding of prostate development and tumorigenesis.

developmental biology↗

bioRxiv2019

A comprehensive genome-scale model for Rhodosporidium toruloides IFO0880 accounting for functional genomics and phenotypic data

BackgroundRhodosporidium toruloides is a basidiomycetes yeast that can accumulate large amount of lipids and natively produce carotenoids. To better assess this non-model yeasts metabolic capabilities, we reconstruct a genome-scale model of R. toruloides IFO0880s metabolic network (iRhto1108) using recent functional genomics and phenotypic data in literature or generated herein.\n\nResultsThe model iRhto1108 accounts for 2,203 reactions, 1,985 metabolites and 1,108 genes. In this work, we integrate and supplement the current knowledge with in-house generated biomass composition and experimental measurements pertaining to the organisms metabolic capabilities. Phenotype-genotype relationship predictions were improved through manual curation of gene-protein-reaction rules for 543 reactions and validations with gene essentiality data leading to correct recapitulations of 84.5% of gene essentiality data (sensitivity of 94.3% and specificity of 53.8%). Organism-specific macromolecular composition and ATP maintenance requirements were experimentally measured for two separate growth conditions: (i) carbon and (ii) nitrogen limitations. Overall, iRhto1108 reproduced R. toruloidess utilization capabilities for 18 alternate substrates, matched measured wild-type growth yield, and recapitulated the viability of 772 out of 819 deletion mutants. As a demonstration to the models fidelity in guiding engineering interventions, the OptForce procedure was applied on iRhto1108 for the overproduction of triacylglycerol. Suggested interventions recapitulated many of the previously successfully implemented genetic modifications and put forth a few new ones.\n\nConclusioniRhto1108 offers a highly curated model for a non-model yeast supported by multiple layers of experimental data that can be used to inform genetic interventions.

systems biology↗

bioRxiv2019

Coloring Single Nanoparticle Trajectory on Live Cell Membrane with its Own History: a Presuppositionless Approach

Analyzing single particle trajectories is a prominent issue in understanding complex dynamics such as nanoparticle-cell interactions. Existing methods treat data points as isolated \"atoms\" and use predefined mechanical models to \"frame\" their complicated relationship. Herein, we propose a \"historical evolution\" based model-free strategy. It allows spatiotemporal heterogeneity embedded in a trajectory to self-emerge as consecutive colored segments before any model assumption, provide both an overall picture and local state transitions on the particle movement with minimum information loss, and inspire further model-based investigation. We demonstrate with simulations and experiments that the underlying mechanisms of various time-series and motion states of single nanoparticles on live cell membranes could all be revealed successfully. Since complexity studies at different levels of molecules, particles, cells, human beings, vehicles, and even stars could all be reduced to analyzing spatiotemporal trajectories of \"single particles\", this presuppositionless approach will help fundamental researches on many important systems.\n\nImpact StatementA preprocessing strategy for single particle trajectory analysis is established by providing an intuitive global pattern from \"historical experiences\" of the particle without predefining any mechanical models.

biophysics↗

bioRxiv2019

Impact of Prior Cancer on Outcomes in Nasopharyngeal Carcinoma

BackgroundPrior cancer is a common exclusion criterion in nasopharyngeal carcinoma (NPC) trials. However, whether a prior cancer diagnosis affects trial outcomes is still unknown. We aimed to determine the impact of prior cancer on survival in NPC. MethodsWe identified patients diagnosed with NPC between 2004 and 2009 in the Surveillance, Epidemiology, and End Results (SEER) database. Variables were compared by chi-squared test and t-test as appropriate. Propensity score-adjusted Kaplan-Meier methods and Cox proportional hazard models were used to evaluate the impact of prior cancer on overall survival (OS). ResultsAmong 3,131 eligible NPC patients, 349 (11.15%) patients had a history of prior cancer. The Kaplan-Meier curves did not show a statistically significantly different OS (p=0.19). Subgroup analyses stratified by timing of prior cancer and AJCC TNM stage of index cancer displayed the same tendency, prior cancer didnt adversely affect OS compared with patients without prior cancer (p>0.05). Furthermore, in propensity score-adjusted COX models analysis, patients with prior cancer had the same/non-inferior OS (hazard ratio [HR] = 1.12, 95% confidence interval= 0.88 to 1.42). ConclusionsAmong patients with nasopharyngeal carcinoma, prior cancer does not convey an adverse effect on clinical outcomes, regardless of the timing of prior cancer and AJCC TNM stage of index cancer. Broader inclusion trial criteria could be adopted in nasopharyngeal carcinoma patients with a history of prior cancer. However, further studies are still needed to confirm.

epidemiology↗

bioRxiv2019

Genome-wide Association Study of Alcohol Consumption and Use Disorder in Multiple Populations (N = 274,424)

Although alcohol consumption level and alcohol use disorder (AUD) diagnosis are both moderately heritable, their genetic risks and overlap are not well understood. We conducted genome-wide association studies of these traits using longitudinal Alcohol Use Disorder Identification Test-Consumption (AUDIT-C) scores (reflecting alcohol consumption) and AUD diagnoses from electronic health records (EHRs) in a single, large multi-ancestry Million Veteran Program sample. Meta-analysis across population groups (N = 274,424) identified 18 genome-wide significant loci, 5 of which were associated with both traits and 13 with either AUDIT-C (N = 8) or AUD (N = 5). A significant genetic correlation between the traits reflects this overlap. However, downstream analyses revealed biologically meaningful points of divergence. Cell-type group partitioning heritability enrichment analyses indicated that central nervous system was the most significant cell type for AUDIT-C and the only significant cell type for AUD. Polygenic risk scores (PRS) for both traits were associated with alcohol-related disorders in two independent samples. Genetic correlations for 188 non-alcohol-related traits were significantly different for the two traits, as were the phenotypes associated with the traits polygenic risk scores. We conclude that EHR-derived, longitudinal, repeated measures of alcohol consumption level and AUD diagnosis can facilitate genetic discovery and help to elucidate the relationship between drinking level and AUD risk. Finally, although heavy drinking is a key risk factor for AUD, it is not a sufficient cause of the disorder.

genetics↗

bioRxiv2019

Leveraging tissue specific gene expression regulation to identify genes associated with complex diseases

To increase statistical power to identify genes associated with complex traits, a number of transcriptome-wide association study (TWAS) methods have been proposed using gene expression as a mediating trait linking genetic variations and diseases. These methods first predict expression levels based on inferred expression quantitative trait loci (eQTLs) and then identify expression-mediated genetic effects on diseases by associating phenotypes with predicted expression levels. The success of these methods critically depends on the identification of eQTLs, which may not be functional in the corresponding tissue, due to linkage disequilibrium (LD) and the correlation of gene expression between tissues. Here, we introduce a new method called T-GEN (Transcriptome-mediated identification of disease-associated Gens with Epigenetic aNnotation) to identify disease-associated genes leveraging epigenetic information. Through prioritizing SNPs with tissue-specific epigenetic annotation, T-GEN can better identify SNPs that are both statistically predictive and biologically functional. We found that a significantly higher percentage (an increase of 18.7% to 47.2%) of eQTLs identified by T-GEN are inferred to be functional by ChromHMM and more are deleterious based on their Combined Annotation Dependent Depletion (CADD) scores. Applying T-GEN to 207 complex traits, we were able to identify more trait-associated genes (ranging from 7.7 % to 102%) than those from existing methods. Among the identified genes associated with these traits, T-GEN can better identify genes with high (>0.99) pLI scores compared to other methods. When T-GEN was applied to late-onset Alzheimers disease, we identified 96 genes located at 15 loci, including two novel loci not implicated in previous GWAS. We further replicated 50 genes in an independent GWAS, including one of the two novel loci. Author summaryTWAS-like methods have been widely applied to understand disease etiology using eQTL data and GWAS results. However, it is still challenging to discriminate the true disease-associated genes from those in strong LD with true genes, which is largely due to the misidentification of eQTLs. Here we introduce a novel statistical method named T-GEN to identify disease-associated genes considering epigenetic information. Compared to current TWAS methods, T-GEN can not only identify eQTLs with higher CADD scores and function potentials in gene-expression imputation models, but also identify more disease-associated genes across 207 traits and more genes with high (>0.99) pLI scores. Applying T-GEN in late-onset Alzheimers disease identified 96 genes at 15 loci with two novel loci. Among 96 identified genes, 50 genes were further replicated in an independent GWAS.

genetics↗

bioRxiv2019

Characterization of Cas proteins for CRISPR-Cas editing in streptomycetes

Application of the well-characterized Streptococcus pyogenes CRISPR-Cas9 system in actinomycetes has enabled high efficiency multiplex genome editing and CRISPRi-mediated transcriptional regulation in these prolific bioactive metabolite producers. Nonetheless, SpCas9 has its limitations and can be ineffective depending on the strains and target sites. Here, we built and tested alternative CRISPR-Cas constructs based on the standalone pCRISPomyces-2 editing plasmid. We showed that Streptococcus thermophilus CRISPR1 (sth1Cas9), Staphylococcus aureus Cas9 (saCas9), and Francisella tularensis subsp. Novicida U112 Cpf1 (fnCpf1) are functional in multiple streptomycetes enabling efficient homology directed repair (HDR)-mediated knock-in and deletion. In strains where spCas9 was non-functional, these alternative Cas systems enabled precise genomic modifications within biosynthetic gene clusters for the discovery, production and diversification of natural products. These additional Cas proteins provide us with the versatility to overcome the limitations of individual CRISPR-Cas systems for genome editing and transcriptional regulation of these industrially important bacteria.

synthetic biology↗