An aptamer-mediated base editing platform for simultaneous knockin and multiple gene knockout for allogeneic CAR-T cells generation.

Gene editing technologies hold promise for enabling the next generation of adoptive cellular therapies. In conventional gene editing platforms that rely on nuclease activity, such as clustered regularly interspaced short palindromic repeats CRISPR-associated protein 9 (CRISPR-Cas9), allow efficient introduction of genetic modifications; however, these modifications occur via the generation of DNA double-strand breaks (DSBs) and can lead to unwanted genomic alterations and genotoxicity. Here, we apply a novel modular RNA aptamer-mediated Pin-point base editing platform to simultaneously introduce multiple gene knockouts and site-specific integration of a transgene in human primary T cells. We demonstrate high editing efficiency and purity at all target sites and significantly reduced frequency of chromosomal translocations compared with the conventional CRISPR-Cas9 system. Site-specific knockin of a chimeric antigen receptor and multiplex gene knockout are achieved within a single intervention and without the requirement for additional sequence-targeting components. The ability to perform complex genome editing efficiently and precisely highlights the potential of the Pin-point platform for application in a range of advanced cell therapies.

A Novel CRISPR Interference Effector Enabling Functional Gene Characterization with Synthetic Guide RNAs.

While CRISPR interference (CRISPRi) systems have been widely implemented in pooled lentiviral screening, there has been limited use with synthetic guide RNAs for the complex phenotypic readouts enabled by experiments in arrayed format. Here we describe a novel deactivated Cas9 fusion protein, dCas9-SALL1-SDS3, which produces greater target gene repression than first or second generation CRISPRi systems when used with chemically modified synthetic single guide RNAs (sgRNAs), while exhibiting high target specificity. We show that dCas9-SALL1-SDS3 interacts with key members of the histone deacetylase and Swi-independent three complexes, which are the endogenous functional effectors of SALL1 and SDS3. Synthetic sgRNAs can also be used with in vitro-transcribed dCas9-SALL1-SDS3 mRNA for short-term delivery into primary cells, including human induced pluripotent stem cells and primary T cells. Finally, we used dCas9-SALL1-SDS3 for functional gene characterization of DNA damage host factors, orthogonally to small interfering RNA, demonstrating the ability of the system to be used in arrayed-format screening.

Development and Characterization of a Modular CRISPR and RNA Aptamer Mediated Base Editing System.

Conventional CRISPR approaches for precision genome editing rely on the introduction of DNA double-strand breaks (DSB) and activation of homology-directed repair (HDR), which is inherently genotoxic and inefficient in somatic cells. The development of base editing (BE) systems that edit a target base without requiring generation of DSB or HDR offers an alternative. Here, we describe a novel BE system called Pin-pointTM that recruits a DNA base-modifying enzyme through an RNA aptamer within the gRNA molecule. Pin-point is capable of efficiently modifying base pairs in the human genome with precision and low on-target indel formation. This system can potentially be applied for correcting pathogenic mutations, installing premature stop codons in pathological genes, and introducing other types of genetic changes for basic research and therapeutic development.

CRISPR-mediated transcriptional activation with synthetic guide RNA.

The CRISPR-Cas9 system has been adapted for transcriptional activation (CRISPRa) and several second-generation CRISPRa systems (including VPR, SunTag, and SAM) have been developed to recruit different transcriptional activators to a deactivated Cas9, which is guided to a transcriptional start site via base complementarity with a target guide RNA. Multiple studies have shown the benefit of CRISPRa using plasmid or lentiviral expressed guide RNA, but the use of synthetic guide RNA has not been reported. Here we demonstrate the effective use of synthetic guide RNA for gene activation via CRISPRa. CRISPRa crRNA may be used with a canonical tracrRNA using the VPR or SunTag activation systems or with an extended tracrRNA containing an aptamer sequence for the SAM system. Transcriptional activation with synthetic crRNA:tracrRNA is comparable to activation achieved with expression vectors and combining several crRNA sequences targeting the same gene can enhance transcriptional activation. The use of synthetic crRNA is also ideal for simultaneous activation of multiple genes or use with dCas9-VPR mRNA when viral transduction is not feasible. Here, we perform a proof-of-principle arrayed screen using a CRISPRa crRNA library consisting of 153 cytokine receptor targets to identify regulators of IL-6 cytokine secretion. Together, these results demonstrate the suitability of synthetic CRISPRa guide RNA for high throughput, arrayed screening applications which allow for more complex phenotypic readouts to complement viability and drug resistance assays typically used in a pooled screening format.

The Power Decoder Simulator for the Evaluation of Pooled shRNA Screen Performance.

RNA interference screening using pooled, short hairpin RNA (shRNA) is a powerful, high-throughput tool for determining the biological relevance of genes for a phenotype. Assessing an shRNA pooled screen's performance is difficult in practice; one can estimate the performance only by using reproducibility as a proxy for power or by employing a large number of validated positive and negative controls. Here, we develop an open-source software tool, the Power Decoder simulator, for generating shRNA pooled screening experiments in silico that can be used to estimate a screen's statistical power. Using the negative binomial distribution, it models both the relative abundance of multiple shRNAs within a single screening replicate and the biological noise between replicates for each individual shRNA. We demonstrate that this simulator can successfully model the data from an actual laboratory experiment. We then use it to evaluate the effects of biological replicates and sequencing counts on the performance of a pooled screen, without the necessity of gathering additional data. The Power Decoder simulator is written in R and Python and is available for download under the GNU General Public License v3.0.

Meta-analyses of studies of the human microbiota.

Our body habitat-associated microbial communities are of intense research interest because of their influence on human health. Because many studies of the microbiota are based on the same bacterial 16S ribosomal RNA (rRNA) gene target, they can, in principle, be compared to determine the relative importance of different disease/physiologic/developmental states. However, differences in experimental protocols used may produce variation that outweighs biological differences. By comparing 16S rRNA gene sequences generated from diverse studies of the human microbiota using the QIIME database, we found that variation in composition of the microbiota across different body sites was consistently larger than technical variability across studies. However, samples from different studies of the Western adult fecal microbiota generally clustered by study, and the 16S rRNA target region, DNA extraction technique, and sequencing platform produced systematic biases in observed diversity that could obscure biologically meaningful compositional differences. In contrast, systematic compositional differences in the fecal microbiota that occurred with age and between Western and more agrarian cultures were great enough to outweigh technical variation. Furthermore, individuals with ileal Crohn's disease and in their third trimester of pregnancy often resembled infants from different studies more than controls from the same study, indicating parallel compositional attributes of these distinct developmental/physiological/disease states. Together, these results show that cross-study comparisons of human microbiota are valuable when the studied parameter has a large effect size, but studies of more subtle effects on the human microbiota require carefully selected control populations and standardized protocols.

Widespread colonization of the lung by Tropheryma whipplei in HIV infection.

RATIONALE: Lung infections caused by opportunistic or virulent pathogens are a principal cause of morbidity and mortality in HIV infection. It is unknown whether HIV infection leads to changes in basal lung microflora, which may contribute to chronic pulmonary complications that increasingly are being recognized in individuals infected with HIV. OBJECTIVES: To determine whether the immunodeficiency associated with HIV infection resulted in alteration of the lung microbiota. METHODS: We used 16S ribosomal RNA targeted pyrosequencing and shotgun metagenomic sequencing to analyze bacterial gene sequences in bronchoalveolar lavage (BAL) and mouths of 82 HIV-positive and 77 HIV-negative subjects. MEASUREMENTS AND MAIN RESULTS: Sequences representing Tropheryma whipplei, the etiologic agent of Whipple's disease, were significantly more frequent in BAL of HIV-positive compared with HIV-negative individuals. T. whipplei dominated the community (>50% of sequence reads) in 11 HIV-positive subjects, but only 1 HIV-negative individual (13.4 versus 1.3%; P = 0.0018). In 30 HIV-positive individuals sampled longitudinally, antiretroviral therapy resulted in a significantly reduced relative abundance of T. whipplei in the lung. Shotgun metagenomic sequencing was performed on eight BAL samples dominated by T. whipplei 16S ribosomal RNA. Whole genome assembly of pooled reads showed that uncultured lung-derived T. whipplei had similar gene content to two isolates obtained from subjects with Whipple's disease. CONCLUSIONS: Asymptomatic subjects with HIV infection have unexpected colonization of the lung by T. whipplei, which is reduced by effective antiretroviral therapy and merits further study for a potential pathogenic role in chronic pulmonary complications of HIV infection.

Using QIIME to analyze 16S rRNA gene sequences from microbial communities.

QIIME (canonically pronounced "chime") is a software application that performs microbial community analysis. It is an acronym for Quantitative Insights Into Microbial Ecology, and has been used to analyze and interpret nucleic acid sequence data from fungal, viral, bacterial, and archaeal communities. The following protocols describe how to install QIIME on a single computer and use it to analyze microbial 16S sequence data from nine distinct microbial communities.

Diversity, stability and resilience of the human gut microbiota.

Trillions of microbes inhabit the human intestine, forming a complex ecological community that influences normal physiology and susceptibility to disease through its collective metabolic activities and host interactions. Understanding the factors that underlie changes in the composition and function of the gut microbiota will aid in the design of therapies that target it. This goal is formidable. The gut microbiota is immensely diverse, varies between individuals and can fluctuate over time - especially during disease and early development. Viewing the microbiota from an ecological perspective could provide insight into how to promote health by targeting this microbial community in clinical treatments.

Microbiota regulate intestinal absorption and metabolism of fatty acids in the zebrafish.

Regulation of intestinal dietary fat absorption is critical to maintaining energy balance. While intestinal microbiota clearly impact the host's energy balance, their role in intestinal absorption and extraintestinal metabolism of dietary fat is less clear. Using in vivo imaging of fluorescent fatty acid (FA) analogs delivered to gnotobiotic zebrafish hosts, we reveal that microbiota stimulate FA uptake and lipid droplet (LD) formation in the intestinal epithelium and liver. Microbiota increase epithelial LD number in a diet-dependent manner. The presence of food led to the intestinal enrichment of bacteria from the phylum Firmicutes. Diet-enriched Firmicutes and their products were sufficient to increase epithelial LD number, whereas LD size was increased by other bacterial types. Thus, different members of the intestinal microbiota promote FA absorption via distinct mechanisms. Diet-induced alterations in microbiota composition might influence fat absorption, providing mechanistic insight into how microbiota-diet interactions regulate host energy balance.

Lake microbial communities are resilient after a whole-ecosystem disturbance.

Disturbances act as powerful structuring forces on ecosystems. To ask whether environmental microbial communities have capacity to recover after a large disturbance event, we conducted a whole-ecosystem manipulation, during which we imposed an intense disturbance on freshwater microbial communities by artificially mixing a temperate lake during peak summer thermal stratification. We employed environmental sensors and water chemistry analyses to evaluate the physical and chemical responses of the lake, and bar-coded 16S ribosomal RNA gene pyrosequencing and automated ribosomal intergenic spacer analysis (ARISA) to assess the bacterial community responses. The artificial mixing increased mean lake temperature from 14 to 20 °C for seven weeks after mixing ended, and exposed the microorganisms to very different environmental conditions, including increased hypolimnion oxygen and increased epilimnion carbon dioxide concentrations. Though overall ecosystem conditions remained altered (with hypolimnion temperatures elevated from 6 to 20 °C), bacterial communities returned to their pre-manipulation state as some environmental conditions, such as oxygen concentration, recovered. Recovery to pre-disturbance community composition and diversity was observed within 7 (epilimnion) and 11 (hypolimnion) days after mixing. Our results suggest that some microbial communities have capacity to recover after a major disturbance.

RNASTAR: an RNA STructural Alignment Repository that provides insight into the evolution of natural and artificial RNAs.

Automated RNA alignment algorithms often fail to recapture the essential conserved sites that are critical for function. To assist in the refinement of these algorithms, we manually curated a set of 148 alignments with a total of 9600 unique sequences, in which each alignment was backed by at least one crystal or NMR structure. These alignments included both naturally and artificially selected molecules. We used principles of isostericity to improve the alignments from an average of 83%-94% isosteric base pairs. We expect that this alignment collection will assist in a wide range of benchmarking efforts and provide new insight into evolutionary principles governing change in RNA structural motifs. The improved alignments have been contributed to the Rfam database.

The Biological Observation Matrix (BIOM) format or: how I learned to stop worrying and love the ome-ome.

BACKGROUND: We present the Biological Observation Matrix (BIOM, pronounced "biome") format: a JSON-based file format for representing arbitrary observation by sample contingency tables with associated sample and observation metadata. As the number of categories of comparative omics data types (collectively, the "ome-ome") grows rapidly, a general format to represent and archive this data will facilitate the interoperability of existing bioinformatics tools and future meta-analyses. FINDINGS: The BIOM file format is supported by an independent open-source software project (the biom-format project), which initially contains Python objects that support the use and manipulation of BIOM data in Python programs, and is intended to be an open development effort where developers can submit implementations of these objects in other programming languages. CONCLUSIONS: The BIOM file format and the biom-format project are steps toward reducing the "bioinformatics bottleneck" that is currently being experienced in diverse areas of biological sciences, and will help us move toward the next phase of comparative omics where basic science is translated into clinical and environmental applications. The BIOM file format is currently recognized as an Earth Microbiome Project Standard, and as a Candidate Standard by the Genomic Standards Consortium.

Responses of gut microbiota to diet composition and weight loss in lean and obese mice.

Maintenance of a reduced body weight is accompanied by a decrease in energy expenditure beyond that accounted for by reduced body mass and composition, as well as by an increased drive to eat. These effects appear to be due--in part--to reductions in circulating leptin concentrations due to loss of body fat. Gut microbiota have been implicated in the regulation of body weight. The effects of weight loss on qualitative aspects of gut microbiota have been studied in humans and mice, but these studies have been confounded by concurrent changes in diet composition, which influence microbial community composition. We studied the impact of 20% weight loss on the microbiota of diet-induced obese (DIO: 60% calories fat) mice on a high-fat diet (HFD). Weight-reduced DIO (DIO-WR) mice had the same body weight and composition as control (CON) ad-libitum (AL) fed mice being fed a control diet (10% calories fat), allowing a direct comparison of diet and weight-perturbation effects. Microbial community composition was assessed by pyrosequencing 16S rRNA genes derived from the ceca of sacrificed animals. There was a strong effect of diet composition on the diversity and composition of the microbiota. The relative abundance of specific members of the microbiota was correlated with circulating leptin concentrations and gene expression levels of inflammation markers in subcutaneous white adipose tissue in all mice. Together, these results suggest that both host adiposity and diet composition impact microbiota composition, possibly through leptin-mediated regulation of mucus production and/or inflammatory processes that alter the gut habitat.

SitePainter: a tool for exploring biogeographical patterns.

UNLABELLED: As microbial ecologists take advantage of high-throughput analytical techniques to describe microbial communities across ever-increasing numbers of samples, the need for new analysis tools that reveal the intrinsic spatial patterns and structures of these populations is crucial. Here we present SitePainter, an interactive graphical tool that allows investigators to create or upload pictures of their study site, load diversity analyses data and display both diversity and taxonomy results in a spatial context. Features of SitePainter include: visualizing α -diversity, using taxonomic summaries; visualizing ß -diversity, using results from multidimensional scaling methods; and animating relationships among microbial taxa or pathways overtime. SitePainter thus increases the visual power and ability to explore spatially explicit studies. AVAILABILITY: https://sourceforge.net/projects/sitepainter SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: antoniog@colorado.edu, Rob.Knight@colorado.edu.

Comprehensive survey and geometric classification of base triples in RNA structures.

Base triples are recurrent clusters of three RNA nucleobases interacting edge-to-edge by hydrogen bonding. We find that the central base in almost all triples forms base pairs with the other two bases of the triple, providing a natural way to geometrically classify base triples. Given 12 geometric base pair families defined by the Leontis-Westhof nomenclature, combinatoric enumeration predicts 108 potential geometric base triple families. We searched representative atomic-resolution RNA 3D structures and found instances of 68 of the 108 predicted base triple families. Model building suggests that some of the remaining 40 families may be unlikely to form for steric reasons. We developed an on-line resource that provides exemplars of all base triples observed in the structure database and models for unobserved, predicted triples, grouped by triple family, as well as by three-base combination (http://rna.bgsu.edu/Triples). The classification helps to identify recurrent triple motifs that can substitute for each other while conserving RNA 3D structure, with applications in RNA 3D structure prediction and analysis of RNA sequence evolution.

Microbial biogeography of public restroom surfaces.

We spend the majority of our lives indoors where we are constantly exposed to bacteria residing on surfaces. However, the diversity of these surface-associated communities is largely unknown. We explored the biogeographical patterns exhibited by bacteria across ten surfaces within each of twelve public restrooms. Using high-throughput barcoded pyrosequencing of the 16 S rRNA gene, we identified 19 bacterial phyla across all surfaces. Most sequences belonged to four phyla: Actinobacteria, Bacteriodetes, Firmicutes and Proteobacteria. The communities clustered into three general categories: those found on surfaces associated with toilets, those on the restroom floor, and those found on surfaces routinely touched with hands. On toilet surfaces, gut-associated taxa were more prevalent, suggesting fecal contamination of these surfaces. Floor surfaces were the most diverse of all communities and contained several taxa commonly found in soils. Skin-associated bacteria, especially the Propionibacteriaceae, dominated surfaces routinely touched with our hands. Certain taxa were more common in female than in male restrooms as vagina-associated Lactobacillaceae were widely distributed in female restrooms, likely from urine contamination. Use of the SourceTracker algorithm confirmed many of our taxonomic observations as human skin was the primary source of bacteria on restroom surfaces. Overall, these results demonstrate that restroom surfaces host relatively diverse microbial communities dominated by human-associated bacteria with clear linkages between communities on or in different body sites and those communities found on restroom surfaces. More generally, this work is relevant to the public health field as we show that human-associated microbes are commonly found on restroom surfaces suggesting that bacterial pathogens could readily be transmitted between individuals by the touching of surfaces. Furthermore, we demonstrate that we can use high-throughput analyses of bacterial communities to determine sources of bacteria on indoor surfaces, an approach which could be used to track pathogen transmission and test the efficacy of hygiene practices.

Using QIIME to analyze 16S rRNA gene sequences from microbial communities.

QIIME (canonically pronounced "chime") is a software application that performs microbial community analysis. It is an acronym for Quantitative Insights Into Microbial Ecology, and has been used to analyze and interpret nucleic acid sequence data from fungal, viral, bacterial, and archaeal communities. The following protocols describe how to install QIIME on a single computer and use it to analyze microbial 16S sequence data from nine distinct microbial communities.

TopiaryExplorer: visualizing large phylogenetic trees with environmental metadata.

MOTIVATION: Microbial community profiling is a highly active area of research, but tools that facilitate visualization of phylogenetic trees and associated environmental data have not kept up with the increasing quantity of data generated in these studies. RESULTS: TopiaryExplorer supports the visualization of very large phylogenetic trees, including features such as the automated coloring of branches by environmental data, manipulation of trees and incorporation of per-tip metadata (e.g. taxonomic labels). AVAILABILITY: http://topiaryexplorer.sourceforge.net. CONTACT: rob.knight@colorado.edu.

Combined phylogenetic and genomic approaches for the high-throughput study of microbial habitat adaptation.

High-throughput sequencing technologies provide new opportunities to address longstanding questions about habitat adaptation in microbial organisms. How have microbes managed to adapt to such a wide range of environments, and what genomic features allow for such adaptation? We review recent large-scale studies of habitat adaptation, with emphasis on those that utilize phylogenetic techniques. On the basis of current trends, we summarize methodological challenges faced by investigators, and the tools, techniques and analytical approaches available to overcome them. Phylogenetic approaches and detailed information about each environmental sample will be crucial as the ability to collect genome sequences continues to expand.