A Comprehensive, CRISPR-based Functional Analysis of Essential Genes in Bacteria.

Essential gene functions underpin the core reactions required for cell viability, but their contributions and relationships are poorly studied in vivo. Using CRISPR interference, we created knockdowns of every essential gene in Bacillus subtilis and probed their phenotypes. Our high-confidence essential gene network, established using chemical genomics, showed extensive interconnections among distantly related processes and identified modes of action for uncharacterized antibiotics. Importantly, mild knockdown of essential gene functions significantly reduced stationary-phase survival without affecting maximal growth rate, suggesting that essential protein levels are set to maximize outgrowth from stationary phase. Finally, high-throughput microscopy indicated that cell morphology is relatively insensitive to mild knockdown but profoundly affected by depletion of gene function, revealing intimate connections between cell growth and shape. Our results provide a framework for systematic investigation of essential gene functions in vivo broadly applicable to diverse microorganisms and amenable to comparative analysis.

Comparison of new computational methods for spatial modelling of malaria.

BACKGROUND: Geostatistical analysis of health data is increasingly used to model spatial variation in malaria prevalence, burden, and other metrics. Traditional inference methods for geostatistical modelling are notoriously computationally intensive, motivating the development of newer, approximate methods for geostatistical analysis or, more broadly, computational modelling of spatial processes. The appeal of faster methods is particularly great as the size of the region and number of spatial locations being modelled increases. METHODS: This work presents an applied comparison of four proposed 'fast' computational methods for spatial modelling and the software provided to implement them-Integrated Nested Laplace Approximation (INLA), tree boosting with Gaussian processes and mixed effect models (GPBoost), Fixed Rank Kriging (FRK) and Spatial Random Forests (SpRF). The four methods are illustrated by estimating malaria prevalence on two different spatial scales-country and continent. The performance of the four methods is compared on these data in terms of accuracy, computation time, and ease of implementation. RESULTS: Two of these methods-SpRF and GPBoost-do not scale well as the data size increases, and so are likely to be infeasible for larger-scale analysis problems. The two remaining methods-INLA and FRK-do scale well computationally, however the resulting model fits are very sensitive to the user's modelling assumptions and parameter choices. The binomial observation distribution commonly used for disease prevalence mapping with INLA fails to account for small-scale overdispersion present in the malaria prevalence data, which can lead to poor predictions. Selection of an appropriate alternative such as the Beta-binomial distribution is required to produce a reliable model fit. The small-scale random effect term in FRK overcomes this pitfall, but FRK model estimates are very reliant on providing a sufficient number and appropriate configuration of basis functions. Unfortunately the computation time for FRK increases rapidly with increasing basis resolution. CONCLUSIONS: INLA and FRK both enable scalable geostatistical modelling of malaria prevalence data. However care must be taken when using both methods to assess the fit of the model to data and plausibility of predictions, in order to select appropriate model assumptions and parameters.

Complex transcriptional modulation with orthogonal and inducible dCas9 regulators.

The ability to dynamically manipulate the transcriptome is important for studying how gene networks direct cellular functions and how network perturbations cause disease. Nuclease-dead CRISPR-dCas9 transcriptional regulators, while offering an approach for controlling individual gene expression, remain incapable of dynamically coordinating complex transcriptional events. Here, we describe a flexible dCas9-based platform for chemical-inducible complex gene regulation. From a screen of chemical- and light-inducible dimerization systems, we identified two potent chemical inducers that mediate efficient gene activation and repression in mammalian cells. We combined these inducers with orthogonal dCas9 regulators to independently control expression of different genes within the same cell. Using this platform, we further devised AND, OR, NAND, and NOR dCas9 logic operators and a diametric regulator that activates gene expression with one inducer and represses with another. This work provides a robust CRISPR-dCas9-based platform for enacting complex transcription programs that is suitable for large-scale transcriptome engineering.

R-loop formation at Snord116 mediates topotecan inhibition of Ube3a-antisense and allele-specific chromatin decondensation.

Prader-Willi syndrome (PWS) and Angelman syndrome (AS) are oppositely imprinted autism-spectrum disorders with known genetic bases, but complex epigenetic mechanisms underlie their pathogenesis. The PWS/AS locus on 15q11-q13 is regulated by an imprinting control region that is maternally methylated and silenced. The PWS imprinting control region is the promoter for a one megabase paternal transcript encoding the ubiquitous protein-coding Snrpn gene and multiple neuron-specific noncoding RNAs, including the PWS-related Snord116 repetitive locus of small nucleolar RNAs and host genes, and the antisense transcript to AS-causing ubiquitin ligase encoding Ube3a (Ube3a-ATS). Neuron-specific transcriptional progression through Ube3a-ATS correlates with paternal Ube3a silencing and chromatin decondensation. Interestingly, topoisomerase inhibitors, including topotecan, were recently identified in an unbiased drug screen for compounds that could reverse the silent paternal allele of Ube3a in neurons, but the mechanism of topotecan action on the PWS/AS locus is unknown. Here, we demonstrate that topotecan treatment stabilizes the formation of RNA:DNA hybrids (R loops) at G-skewed repeat elements within paternal Snord116, corresponding to increased chromatin decondensation and inhibition of Ube3a-ATS expression. Neural precursor cells from paternal Snord116 deletion mice exhibit increased Ube3a-ATS levels in differentiated neurons and show a reduced effect of topotecan compared with wild-type neurons. These results demonstrate that the AS candidate drug topotecan acts predominantly through stabilizing R loops and chromatin decondensation at the paternally expressed PWS Snord116 locus. Our study holds promise for targeted therapies to the Snord116 locus for both AS and PWS.

A Prader-Willi locus lncRNA cloud modulates diurnal genes and energy expenditure.

Prader-Willi syndrome (PWS), a genetic disorder of obesity, intellectual disability and sleep abnormalities, is caused by loss of non-coding RNAs on paternal chromosome 15q11-q13. The imprinted minimal PWS locus encompasses a long non-coding RNA (lncRNA) transcript processed into multiple SNORD116 small nucleolar RNAs and the spliced exons of the host gene, 116HG. However, both the molecular function and the disease relevance of the spliced lncRNA 116HG are unknown. Here, we show that 116HG forms a subnuclear RNA cloud that co-purifies with the transcriptional activator RBBP5 and active metabolic genes, remains tethered to the site of its transcription and increases in size in post-natal neurons and during sleep. Snord116del mice lacking 116HG exhibited increased energy expenditure corresponding to the dysregulation of diurnally expressed Mtor and circadian genes Clock, Cry1 and Per2. These combined genomic and metabolic analyses demonstrate that 116HG regulates the diurnal energy expenditure of the brain. These novel molecular insights into the energy imbalance in PWS should lead to improved therapies and understanding of lncRNA roles in complex neurodevelopmental and metabolic disorders.

Population Density Modulates the Duration of Reproduction of C. elegans.

Population density can modulate the developmental trajectory of Caenorhabditis elegans larvae by promoting entry into dauer diapause, which is characterized by metabolic and anatomical remodeling and stress resistance [1, 2]. Genetic analysis of dauer formation has identified the involvement of evolutionarily conserved endocrine signaling pathways, including the DAF-2/insulin-like receptor signaling pathway [3-7]. Chemical and metabolomic analysis of dauer-inducing pheromone has identified a family of small molecules, ascarosides, which act potently to communicate increased population density and promote dauer formation [1, 8-10]. Here, we show that adult animals respond to ascarosides produced under conditions of increased population density by increasing the duration of reproduction. We observe that the ascarosides that promote dauer entry of larvae also act on adult animals to attenuate expression of the insulin peptide INS-6 from the ASI chemosensory neurons, resulting in diminished neuroendocrine insulin signaling that extends the duration of reproduction. Genetic analysis of ins-6 and corresponding insulin-signaling pathway mutants showed that the effect of increased population density on reproductive span was mimicked by ins-6 loss of function that exerted effects on duration of reproduction through the canonical DAF-2-DAF-16 pathway. We further observed that the effect of population density on reproductive span acted through DAF-16-dependent and DAF-16-independent pathways upstream of DAF-12, paralleling in adults what has been observed for the dauer developmental decision of larvae. Our data suggest that, under conditions of increased population density, C. elegans animals prolong the duration of reproductive egg laying, which may enable the subsequent development of progeny under more favorable conditions.

Targeted Transcriptional Repression in Bacteria Using CRISPR Interference (CRISPRi).

Clustered regularly interspersed short palindromic repeats (CRISPR) interference (CRISPRi) is a powerful technology for sequence-specifically repressing gene expression in bacterial cells. CRISPRi requires only a single protein and a custom-designed guide RNA for specific gene targeting. In Escherichia coli, CRISPRi repression efficiency is high (~300-fold), and there are no observable off-target effects. The method can be scaled up as a general strategy for the repression of many genes simultaneously using multiple designed guide RNAs. Here we provide a protocol for efficient guide RNA design, cloning, and assay of the CRISPRi system in E. coli. In principle, this protocol can be used to construct CRISPRi systems for gene repression in other species of bacteria.