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We generated a library of ~1000 Drosophila stocks in which we inserted a construct in the intron of genes allowing expression of GAL4 under control of endogenous promoters while arresting transcription with a polyadenylation signal 3' of the GAL4. This allows numerous applications. First, ~90% of insertions in essential genes cause a severe loss-of-function phenotype, an effective way to mutagenize genes. Interestingly, 12/14 chromosomes engineered through CRISPR do not carry second-site lethal mutations. Second, 26/36 (70%) of lethal insertions tested are rescued with a single UAS-cDNA construct. Third, loss-of-function phenotypes associated with many GAL4 insertions can be reverted by excision with UAS-flippase. Fourth, GAL4 driven UAS-GFP/RFP reports tissue and cell-type specificity of gene expression with high sensitivity. We report the expression of hundreds of genes not previously reported. Finally, inserted cassettes can be replaced with GFP or any DNA. These stocks comprise a powerful resource for assessing gene function.
The coronavirus (CoV) severe acute respiratory syndrome (SARS)-CoV-2 (COVID-19) pandemic has received rapid response by the research community to offer suggestions for repurposing of approved drugs as well as to improve our understanding of the COVID-19 viral life cycle molecular mechanisms. In a short period, tens of thousands of research preprints and other publications have emerged including those that report lists of experimentally validated drugs and compounds as potential COVID-19 therapies. In addition, gene sets from interacting COVID-19 virus-host proteins and differentially expressed genes when comparing infected to uninfected cells are being published at a fast rate. To organize this rapidly accumulating knowledge, we developed the COVID-19 Gene and Drug Set Library (https://amp.pharm.mssm.edu/covid19/), a collection of gene and drug sets related to COVID-19 research from multiple sources. The COVID-19 Gene and Drug Set Library is delivered as a web-based interface that enables users to view, download, analyze, visualize, and contribute gene and drug sets related to COVID-19 research. To evaluate the content of the library, we performed several analyses including comparing the results from 6 in-vitro drug screens for COVID-19 repurposing candidates. Surprisingly, we observe little overlap across these initial screens. The most common and unique hit across these screen is mefloquine, a malaria drug that should receive more attention as a potential therapeutic for COVID-19. Overall, the library of gene and drug sets can be used to identify community consensus, make researchers and clinicians aware of the development of new potential therapies, as well as allow the research community to work together towards a cure for COVID-19.
The biological interpretation of gene lists with interesting shared properties, such as up- or down-regulation in a particular experiment, is typically accomplished using gene ontology enrichment analysis tools. Given a list of genes, a gene ontology (GO) enrichment analysis may return hundreds of statistically significant GO results in a "flat" list, which can be challenging to summarize. It can also be difficult to keep pace with rapidly expanding biological knowledge, which often results in daily changes to any of the over 47,000 gene ontologies that describe biological knowledge. GOATOOLS, a Python-based library, makes it more efficient to stay current with the latest ontologies and annotations, perform gene ontology enrichment analyses to determine over- and under-represented terms, and organize results for greater clarity and easier interpretation using a novel GOATOOLS GO grouping method. We performed functional analyses on both stochastic simulation data and real data from a published RNA-seq study to compare the enrichment results from GOATOOLS to two other popular tools: DAVID and GOstats. GOATOOLS is freely available through GitHub: https://github.com/tanghaibao/goatools .
Microbial biosynthetic gene clusters are a valuable source of bioactive molecules. However, because they typically represent a small fraction of genomic material in most metagenomic samples, it remains challenging to deeply sequence them. We present an approach to isolate and sequence gene clusters in metagenomic samples using microfluidic automated plasmid library enrichment. Our approach provides deep coverage of the target gene cluster, facilitating reassembly. We demonstrate the approach by isolating and sequencing type I polyketide synthase gene clusters from an Antarctic soil metagenome. Our method promotes the discovery of functional-related genes and biosynthetic pathways.
Balancing protein expression is critical when optimizing genetic systems. Typically, this requires library construction to vary the genetic parts controlling each gene, which can be expensive and time-consuming. Here, we develop sRNAs corresponding to 15nt 'target' sequences that can be inserted upstream of a gene. The targeted gene can be repressed from 1.6- to 87-fold by controlling sRNA expression using promoters of different strength. A pool is built where six sRNAs are placed under the control of 16 promoters that span a ∼103-fold range of strengths, yielding ∼107 combinations. This pool can simultaneously optimize up to six genes in a system. This requires building only a single system-specific construct by placing a target sequence upstream of each gene and transforming it with the pre-built sRNA pool. The resulting library is screened and the top clone is sequenced to determine the promoter controlling each sRNA, from which the fold-repression of the genes can be inferred. The system is then rebuilt by rationally selecting parts that implement the optimal expression of each gene. We demonstrate the versatility of this approach by using the same pool to optimize a metabolic pathway (β-carotene) and genetic circuit (XNOR logic gate).
One key bottleneck in understanding the human genome is the relative under-characterization of 90% of protein coding regions. We report a collection of 1200 transgenic zebrafish strains made with the gene-break transposon (GBT) protein trap to simultaneously report and reversibly knockdown the tagged genes. Protein trap-associated mRFP expression shows previously undocumented expression of 35% and 90% of cloned genes at 2 and 4 days post-fertilization, respectively. Further, investigated alleles regularly show 99% gene-specific mRNA knockdown. Homozygous GBT animals in ryr1b, fras1, tnnt2a, edar and hmcn1 phenocopied established mutants. 204 cloned lines trapped diverse proteins, including 64 orthologs of human disease-associated genes with 40 as potential new disease models. Severely reduced skeletal muscle Ca2+ transients in GBT ryr1b homozygous animals validated the ability to explore molecular mechanisms of genetic diseases. This GBT system facilitates novel functional genome annotation towards understanding cellular and molecular underpinnings of vertebrate biology and human disease.
Leishmaniasis are widespread parasitic-diseases with an urgent need for more active and less toxic drugs and for effective vaccines. Understanding the biology of the parasite especially in the context of host parasite interaction is a crucial step towards such improvements in therapy and control. Several experimental approaches including SAGE (Serial analysis of gene expression) have been developed in order to investigate the parasite transcriptome organisation and plasticity. Usual SAGE tag-to-gene mapping techniques are inadequate because almost all tags are normally located in the 3'-UTR outside the CDS, whereas most information available for Leishmania transcripts is restricted to the CDS predictions. The aim of this work is to optimize a SAGE libraries tag-to-gene mapping technique and to show how this development improves the understanding of Leishmania transcriptome.
Capitalizing on the inherent multiplexing capability of AsCpf1, we developed a multiplexed, high-throughput screening strategy that minimizes library size without sacrificing gene targeting efficiency. We demonstrated that AsCpf1 can be used for functional genomics screenings and that an AsCpf1-based multiplexed library performs similarly as compared to currently available monocistronic CRISPR/Cas9 libraries, with only one vector required for each gene. We construct the smallest whole-genome CRISPR knock-out library, Mini-human, for the human genome (n = 17,032 constructs targeting 16,977 protein-coding genes), which performs favorably compared to conventional Cas9 libraries.
Gene/protein recognition and normalization are important preliminary steps for many biological text mining tasks, such as information retrieval, protein-protein interactions, and extraction of semantic information, among others. Despite dedication to these problems and effective solutions being reported, easily integrated tools to perform these tasks are not readily available.
Soil microorganisms historically have been a rich resource for natural product discovery, yet the majority of these microbes remain uncultivated and their biosynthetic capacity is left underexplored. To identify the biosynthetic potential of soil microorganisms using a culture-independent approach, we constructed a large-insert metagenomic library in Escherichia coli from a topsoil sampled from the Cullars Rotation (Auburn, AL, United States), a long-term crop rotation experiment. Library clones were screened for biosynthetic gene clusters (BGCs) using either PCR or a NGS (next generation sequencing) multiplexed pooling strategy, coupled with bioinformatic analysis to identify contigs associated with each metagenomic clone. A total of 1,015 BGCs were detected from 19,200 clones, identifying 223 clones (1.2%) that carry a polyketide synthase (PKS) and/or a non-ribosomal peptide synthetase (NRPS) cluster, a dramatically improved hit rate compared to PCR screening that targeted type I polyketide ketosynthase (KS) domains. The NRPS and PKS clusters identified by NGS were distinct from known BGCs in the MIBiG database or those PKS clusters identified by PCR. Likewise, 16S rRNA gene sequences obtained by NGS of the library included many representatives that were not recovered by PCR, in concordance with the same bias observed in KS amplicon screening. This study provides novel resources for natural product discovery and circumvents amplification bias to allow annotation of a soil metagenomic library for a more complete picture of its functional and phylogenetic diversity.
Caseous lymphadenitis (CLA) is a disease that affects sheep, goats and occasionally humans. The etiologic agent is the Corynebacterium pseudotuberculosis bacillus. The objective of this study was to build a gene expression library from C. pseudotuberculosis and use immunoscreening to identify genes that encode potential antigenic proteins for the development of DNA and subunit vaccines against CLA.
Fucoidan, the sulfated fucose-rich polysaccharide derived from brown macroalgae, was reported to display some anti-cancer effects in in vitro and in vivo models that included apoptosis and cell cycle arrest. The proposed mechanisms of action involve enhanced immune surveillance and direct pro-apoptotic effects via the activation of cell signaling pathways that remain largely uncharacterized. This study aimed to identify cellular pathways influenced by fucoidan using an unbiased genetic approach to generate additional insights into the anti-cancer effects of fucoidan. Drug⁻gene interactions of Undaria pinnatifida fucoidan were assessed by a systematic screen of the entire set of 4,733 halpoid Saccharomyces cerevsiae gene deletion strains. Some of the findings were confirmed using cell cycle analysis and DNA damage detection in non-immortalized human dermal fibroblasts and colon cancer cells. The yeast deletion library screen and subsequent pathway and interactome analysis identified global effects of fucoidan on a wide range of eukaryotic cellular processes, including RNA metabolism, protein synthesis, sorting, targeting and transport, carbohydrate metabolism, mitochondrial maintenance, cell cycle regulation, and DNA damage repair-related pathways. Fucoidan also reduced clonogenic survival, induced DNA damage and G1-arrest in colon cancer cells, while these effects were not observed in non-immortalized human fibroblasts. Our results demonstrate global effects of fucoidan in diverse cellular processes in eukaryotic cells and further our understanding about the inhibitory effect of Undaria pinnatifida fucoidan on the growth of human cancer cells.
Camelid single-domain antibody fragments (nanobodies) are an emerging force in therapeutic biopharmaceuticals and clinical diagnostic reagents in recent years. Nearly all nanobodies available to date have been obtained by animal immunization, a bottleneck restricting the large-scale application of nanobodies. In this study, we developed three kinds of gene designated-region pan-editing (GDP) technologies to introduce multiple mutations in complementarity-determining regions (CDRs) of nanobodies in vitro. Including the integration of G-quadruplex fragments in CDRs, which induces the spontaneous multiple mutations in CDRs; however, these mutant sequences are highly similar, resulting in a lack of sequences diversity in the CDRs. We also used CDR-targeting traditional gRNA-guided base-editors, which effectively diversify the CDRs. And most importantly, we developed the self-assembling gRNAs, which are generated by reprogrammed tracrRNA hijacking of endogenous mRNAs as crRNAs. Using base-editors guided by self-assembling gRNAs, we can realize the iteratively diversify the CDRs. And we believe the last GDP technology is highly promising in immunization-free nanobody library construction, and the full development of this novel nanobody discovery platform can realize the synthetic evolution of nanobodies in vitro.
Peri-implantitis (PI) is an inflammatory disease which leads to the destruction of soft and hard tissues around osseointegrated implants. The subgingival microbiota appears to be responsible for peri-implant lesions and although the complexity of the microbiota has been reported in PI, the microbiota responsible for PI has not been identified.
Since the discovery of RNA interference (RNAi), small interfering RNA (siRNA) has been powerful tools for gene downregulation in biomedical applications. Despite the outstanding efficacy of siRNA, the development of a therapeutic delivery system remains a challenge owing to the instability of RNA. In this study, we describe a new method for the design of siRNA-generating nanosponges by using complementary rolling circle transcription (cRCT), a technique that requires two complementary circular DNA. The sequences of one of the circular DNA are designed to have complete complementarity to the target mRNA resulting in double stranded RNA (dsRNA) that can be digested to siRNA by cellular Dicer activity. This siRNA design, called 'library siRNA', could be universally applied to fabricate RNA nanosponges targeting any known mRNA sequence.
Combinatorial CRISPR screening is useful for investigating synthetic lethality (SL) gene pairs. Here, we detail the steps for dual-gRNA library construction, with the introduction of two backbones, LentiGuide_DKO and LentiCRISPR_DKO. We describe steps for in vitro screening with 22Rv1-Cas9 and SaOS2-Cas9 cells followed by sequencing and data analysis. By introducing two backbones, we optimized the library construction process, facilitated standard pair-end sequencing, and provided options of screening on cells with or without modification of Cas9 expression.
Quantitative gene expression analysis plays an important role in identifying differentially expressed genes in various pathological states, gene expression regulation and co-regulation, shedding light on gene functions. Although microarray is widely used as a powerful tool in this regard, it is suboptimal quantitatively and unable to detect unknown gene variants. Here we demonstrated effective detection of differential expression and co-regulation of certain genes by expressed sequence tag analysis using a selected subset of cDNA libraries. We discussed the issues of sequencing depth and library preparation, and propose that increased sequencing depth and improved preparation procedures may allow detection of many expression features for less abundant gene variants. With the reduction of sequencing cost and the emerging of new generation sequencing technology, in-depth sequencing of cDNA pools or libraries may represent a better and powerful tool in gene expression profiling and cancer biomarker detection. We also propose using sequence-specific subtraction to remove hundreds of the most abundant housekeeping genes to increase sequencing depth without affecting relative expression ratio of other genes, as transcripts from as few as 300 most abundantly expressed genes constitute about 20% of the total transcriptome. In-depth sequencing also represents a unique advantage of detecting unknown forms of transcripts, such as alternative splicing variants, fusion genes, and regulatory RNAs, as well as detecting mutations and polymorphisms that may play important roles in disease pathogenesis.
MaxDIA is a software platform for analyzing data-independent acquisition (DIA) proteomics data within the MaxQuant software environment. Using spectral libraries, MaxDIA achieves deep proteome coverage with substantially better coefficients of variation in protein quantification than other software. MaxDIA is equipped with accurate false discovery rate (FDR) estimates on both library-to-DIA match and protein levels, including when using whole-proteome predicted spectral libraries. This is the foundation of discovery DIA-hypothesis-free analysis of DIA samples without library and with reliable FDR control. MaxDIA performs three- or four-dimensional feature detection of fragment data, and scoring of matches is augmented by machine learning on the features of an identification. MaxDIA's bootstrap DIA workflow performs multiple rounds of matching with increasing quality of recalibration and stringency of matching to the library. Combining MaxDIA with two new technologies-BoxCar acquisition and trapped ion mobility spectrometry-both lead to deep and accurate proteome quantification.
The narrow-leafed lupin, Lupinus angustifolius L., is a grain legume species with a relatively compact genome. The species has 2n = 40 chromosomes and its genome size is 960 Mbp/1C. During the last decade, L. angustifolius genomic studies have achieved several milestones, such as molecular-marker development, linkage maps, and bacterial artificial chromosome (BAC) libraries. Here, these resources were integratively used to identify and sequence two gene-rich regions (GRRs) of the genome.
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