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BackgroundThe pathological HTT CAG repeat continues to expand throughout life. As CAG repeat length predicts rate of expansion and age of HD onset, slowing expansion is an attractive therapeutic approach. The GeM-HD GWASs associated changes in age of onset with many loci, including DNA damage repair genes. Understanding if/how these risk modifiers affect repeat expansion rate, and their interplay in vulnerable neurons, will contribute to understanding the underlying expansion mechanism.Aims1) Generate a human HD iPSC-based model capable of rapidly assaying risk associated genes for effects on somatic expansion of the HTT CAG repeat in striatal neuron cultures. 2) Target expression of components of the mismatch repair MutL complex (MLH1, PMS1, MLH3 & PMS2) as validation.MethodsdCas9 fused to a transcriptional repressor was knocked-in to the CLYBL safe harbour locus of the 125Q iPSC juvenile HD line. Guides targeting individual MutL components were introduced by lentiviral transduction. Knock-down pools for each gene were differentiated to post-mitotic MSNs and assayed for CAG expansion.ResultsKnock-in clones retained parental CAG expansion rates and differentiation potential. CRISPRi achieved 70-90% reduction in target expression. Knock-down of the individual MutL proteins suppressed expansion in striatal neuron cultures.ConclusionsThis model successfully recapitulates previously reported effects of MutL components on somatic expansion of the HTT CAG repeat. This indicates our model will be a useful platform for rapidly dissecting the effects of other risk modifier gene expression on CAG instability and pathophysiology in a human model of HD.

The increasingly widespread use of next generation sequencing protocols has brought the need for the development of user-friendly raw data processing tools. Here, we explore 2FAST2Q, a versatile and intuitive standalone program capable of extracting and counting feature occurrences in FASTQ files. Despite 2FAST2Q being previously described as part of a CRISPRi-seq analysis pipeline, in here we further elaborate on the program's functionality, and its broader applicability and functions. 2FAST2Q is built in Python, with published standalone executables in Windows MS, MacOS, and Linux. It has a familiar user interface, and uses an advanced custom sequence searching algorithm. Using published CRISPRi datasets in which and gene essentiality, as well as host-cell sensitivity towards SARS-CoV2 infectivity were tested, we demonstrate that 2FAST2Q efficiently recapitulates published output in read counts per provided feature. We further show that 2FAST2Q can be used in any experimental setup that requires feature extraction from raw reads, being able to quickly handle Hamming distance based mismatch alignments, nucleotide wise Phred score filtering, custom read trimming, and sequence searching within a single program. Moreover, we exemplify how different FASTQ read filtering parameters impact downstream analysis, and suggest a default usage protocol. 2FAST2Q is easier to use and faster than currently available tools, efficiently processing not only CRISPRi-seq / random-barcode sequencing datasets on any up-to-date laptop, but also handling the advanced extraction of features from FASTQ files. We expect that 2FAST2Q will not only be useful for people working in microbiology but also for other fields in which amplicon sequencing data is generated. 2FAST2Q is available as an executable file for all current operating systems without installation and as a Python3 module on the PyPI repository (available at https://veeninglab.com/2fast2q).

Reduced genome bacteria are genetically simplified systems that facilitate biological study and industrial use. The free-living alphaproteobacterium Zymomonas mobilis has a naturally reduced genome containing fewer than 2,000 protein-coding genes. Despite its small genome, Z. mobilis thrives in diverse conditions including the presence or absence of atmospheric oxygen. However, insufficient characterization of essential and conditionally essential genes has limited broader adoption of Z. mobilis as a model alphaproteobacterium. Here, we use genome-scale CRISPRi-seq (clustered regularly interspaced short palindromic repeats interference sequencing) to systematically identify and characterize Z. mobilis genes that are conditionally essential for aerotolerant or anaerobic growth or are generally essential across both conditions. Comparative genomics revealed that the essentiality of most “generally essential” genes was shared between Z. mobilis and other Alphaproteobacteria, validating Z. mobilis as a reduced genome model. Among conditionally essential genes, we found that the DNA repair gene, recJ , was critical only for aerobic growth but reduced the mutation rate under both conditions. Further, we show that genes encoding the F 1 F O ATP synthase and R hodobacter n itrogen f ixation (Rnf) respiratory complex are required for the anaerobic growth of Z. mobilis . Combining CRISPRi partial knockdowns with metabolomics and membrane potential measurements, we determined that the ATP synthase generates membrane potential that is consumed by Rnf to power downstream processes. Rnf knockdown strains accumulated isoprenoid biosynthesis intermediates, suggesting a key role for Rnf in powering essential biosynthetic reactions. Our work establishes Z. mobilis as a streamlined model for alphaproteobacterial genetics, has broad implications in bacterial energy coupling, and informs Z. mobilis genome manipulation for optimized production of valuable isoprenoid-based bioproducts. The inherent complexity of biological systems is a major barrier to our understanding of cellular physiology. Bacteria with markedly fewer genes than their close relatives, or reduced genome bacteria, are promising biological models with less complexity. Reduced genome bacteria can also have superior properties for industrial use, provided the reduction does not overly restrict strain robustness. Naturally reduced genome bacteria, such as the alphaproteobacterium Zymomonas mobilis , have fewer genes but remain environmentally robust. In this study, we show that Z. mobilis is a simplified genetic model for Alphaproteobacteria, a class with important impacts on the environment, human health, and industry. We also identify genes that are only required in the absence of atmospheric oxygen, uncovering players that maintain and utilize the cellular energy state. Our findings have broad implications for the genetics of Alphaproteobacteria and industrial use of Z. mobilis to create biofuels and bioproducts.

Streptomyces bacteria are prolific producers of clinically essential natural products, yet high-throughput tools to systematically interrogate their genomes remain underdeveloped. By establishing a robust CRISPRi-seq platform for en masse functional screening in Streptomyces albidoflavus , our work closes a critical technological gap in Streptomyces functional genomics. Our study not only identifies a small subset of transporter operons essential for fitness but also introduces a scalable, generalizable approach for dissecting gene function. This platform will accelerate systems-level understanding of an industrially and medically important genus.

Bacillus subtilis is an industrially important microorganism that is often used as a microbial cell factory for the production of recombinant proteins due to its food safety, rapid growth, and powerful secretory capacity. However, the lack of data on functional genes related to recombinant protein production has hindered the further development of B. subtilis cell factories. Here, a strategy combining genome‐wide CRISPRi screening and targeted CRISPRa activation to enhance recombinant protein expression is proposed. First, a CRISPRi library covering a total of 4225 coding genes (99.7%) in the B. subtilis genome and built the corresponding high‐throughput screening methods is constructed. Twelve key genes for recombinant protein expression are identified, including targets without relevant functional annotations. Meanwhile, the transcription of recombinant protein genes by CRISPRa is up‐regulated. These screened or selected genes can be easily applied to metabolic engineering by constructing sgRNA arrays. The relationship between differential pathways and recombinant protein expression in engineered strains by transcriptome analysis is also revealed. High‐density fermentation and generalisability validation results prove the reliability of the strategy. This method can be extended to other industrial hosts to support functional gene annotation and the design of novel cell factories. Based on genome‐wide CRISPRi screening, 12 repressor genes favorable for recombinant protein production are identified. sgRNA arrays are constructed to combine these novel targets with a CRISPRa‐driven activation strategy to achieve comprehensive multi‐gene regulation. The high‐yielding strains that are obtained have improved the yield of a variety of recombinant proteins.

The clustered regularly interspaced short palindromic repeats/CRISPR-associated (CRISPR/Cas) adaptive immune system has been extensively used for gene editing, including gene deletion, insertion, and replacement in bacterial and eukaryotic cells owing to its simple, rapid, and efficient activities in unprecedented resolution. Furthermore, the CRISPR interference (CRISPRi) system including deactivated Cas9 (dCas9) with inactivated endonuclease activity has been further investigated for regulation of the target gene transiently or constitutively, avoiding cell death by disruption of genome. This review discusses the applications of CRISPR/Cas for genome editing in various bacterial systems and their applications. In particular, CRISPR technology has been used for the production of metabolites of high industrial significance, including biochemical, biofuel, and pharmaceutical products/precursors in bacteria. Here, we focus on methods to increase the productivity and yield/titer scan by controlling metabolic flux through individual or combinatorial use of CRISPR/Cas and CRISPRi systems with introduction of synthetic pathway in industrially common bacteria including Escherichia coli. Further, we discuss additional useful applications of the CRISPR/Cas system, including its use in functional genomics.

Acetogenic bacteria are a unique biocatalyst that highly promises to develop the sustainable bioconversion of carbon oxides (e.g., CO and CO₂) into multicarbon biochemicals. Genotype–phenotype relationships are important for engineering their metabolic capability to enhance their biocatalytic performance; however, systemic investigation on the fitness contribution of individual gene has been limited. Here, we report genome-scale CRISPR interference screening using 41,939 guide RNAs designed from the E. limosum genome, one of the model acetogenic species, where all genes were targeted for transcriptional suppression. We investigated the fitness contributions of 96% of the total genes identified, revealing the gene fitness and essentiality for heterotrophic and autotrophic metabolisms. Our data show that the Wood–Ljungdahl pathway, membrane regeneration, membrane protein biosynthesis, and butyrate synthesis are essential for autotrophic acetogenesis in E. limosum. Furthermore, we discovered genes that are repression targets that unbiasedly increased autotrophic growth rates fourfold and acetoin production 1.5-fold compared to the wild-type strain under CO₂-H₂ conditions. These results provide insight for understanding acetogenic metabolism and genome engineering in acetogenic bacteria.

Background Long non-coding RNAs (lncRNAs) comprise a diverse class of transcripts that can regulate molecular and cellular processes in brain development and disease. LncRNAs exhibit cell type- and tissue-specific expression, but little is known about the expression and function of lncRNAs in the developing human brain. Furthermore, it has been unclear whether lncRNAs are highly expressed in subsets of cells within tissues, despite appearing lowly expressed in bulk populations. Results We use strand-specific RNA-seq to deeply profile lncRNAs from polyadenylated and total RNA obtained from human neocortex at different stages of development, and we apply this reference to analyze the transcriptomes of single cells. While lncRNAs are generally detected at low levels in bulk tissues, single-cell transcriptomics of hundreds of neocortex cells reveal that many lncRNAs are abundantly expressed in individual cells and are cell type-specific. Notably, LOC646329 is a lncRNA enriched in single radial glia cells but is detected at low abundance in tissues. CRISPRi knockdown of LOC646329 indicates that this lncRNA regulates cell proliferation. Conclusion The discrete and abundant expression of lncRNAs among individual cells has important implications for both their biological function and utility for distinguishing neural cell types.

High-throughput genetic screens interfering with gene expression are invaluable tools to identify gene function and phenotype-to-genotype interactions. Implementing such screens in the laboratory is challenging, and the choice between currently available technologies based on RNAi and CRISPR/Cas9 (CRISPR-associated protein 9) is not trivial. Identifying reliable candidate hits requires a streamlined experimental setup adjusted to the specific biological question. Here, we provide a critical assessment of the various RNAi/CRISPR approaches to pooled screens and discuss their advantages and pitfalls. We specify a set of best practices for key parameters enabling a reproducible screen and provide a detailed overview of analysis methods and repositories for identifying the best candidate gene hits. Pooled genetic screens based on RNAi and CRISPR technologies are a powerful approach for high-throughput interrogation of loss- or gain-of-function and phenotype-to-genotype correlations. Several CRISPR technologies are applicable for pooled screens, allowing for a wide range of genetic perturbations and mutagenesis beyond classical RNAi-based gene knockdown. Stringent experimental design, appropriate controls and careful library selection are essential to identify valid hits. Appropriate library representation throughout the screening procedure is key to avoid false positives/negatives. Different bioinformatics pipelines can be applied to data analysis, and their combination may lead to increased specificity of selected hits.

The mitogen-activated protein kinase pathway (MAPK) transduces signals to affect a variety of biological processes, including, proliferation, differentiation, and cellular survival. It is known to be key during cardiovascular development and during physiological cardiovascular function, indicated by the congenital heart defects that are typical of Noonan syndrome and other diseases that affect MAPK signalling. A previous group have shown that a long non-coding RNA, the EGF-inducible non-coding RNA 1 (EINCR1) regulates the MEK/ERK branch of the MAPK pathway, which usually responds to growth factors and other mitogenic signals. However, the exact mechanism is unknown. Due to the importance of the MEK/ERK pathway in various cardiovascular physiological and pathological processes, and because EINCR1 expression is highest in the heart, we wanted to investigate how EINCR1 regulates the MEK/ERK kinase cascade. Current pharmacological inhibitors of the MEK/ERK pathway have significant side effects, and the identification of alternative regulatory mechanisms could prove to be beneficial for patients with a variety of diseases. In the first phase of this study, we had three main aims. First, to confirm that EINCR1 expression is induced by MAPK activation via EGF treatment and transfection with a constitutively active MEK. Second, to characterise the EINCR1 locus using Nanopore long-read sequencing because previous studies have suggested that the current gene annotation is not complete. Finally, we aimed to identify any enhancers in the locus that could be contributing to its regulatory effects, and once identified, to use CRISPRi to downregulate the activity of these enhancers and use RT-qPCR to identify the genes affected. First, we confirmed that EINCR1 expression is induced following EGF treatment. Nanopore sequencing then revealed that the transcripts that arise from the EINCR1 locus are not well defined, with no consistent spliced structure, like other lncRNAs, such as MALAT1. The enhancer assays indicated that two regions near the EINCR1 locus have potential enhancer ability when compared to a random region of DNA that was used as a control. Our initial findings indicate that MAPK signalling activates enhancers near and within the EINCR1 gene body. Nanopore sequencing revealed that the EINCR1 transcript lacks a consistent splicing pattern in a bladder cancer cell line. However, future studies are aimed at assessing the structure of the EINCR1 transcript in the heart, as there is some evidence that suggests it may be consistently spliced in the cardiomyocytes. A consistent structure in the heart may indicate that the transcript is functional in addition to the enhancers. Analysis of our CRISPRi work is ongoing, and we hope to identify genes that are regulated by this locus soon. Understanding the entire MAPK signalling pathway, including its regulatory mechanisms, could be key in the prevention of disease and for the development of novel treatments of cardiovascular diseases.