Conditional CRISPR-Cas Genome Editing in Drosophila to Generate Intestinal Tumors

CRISPR-Cas has revolutionized genetics and extensive efforts have been made to enhance its editing efficiency by developing increasingly more elaborate tools. Here, we evaluate the CRISPR-Cas9 system in Drosophila melanogaster to assess its ability to induce stem cell-derived tumors in the intestine. We generated conditional tissue-specific CRISPR knockouts using different Cas9 expression vectors with guide RNAs targeting the BMP, Notch, and JNK pathways in intestinal progenitors such as stem cells (ISCs) and enteroblasts (EBs). Perturbing Notch and BMP signaling increased the proliferation of ISCs/EBs and resulted in the formation of intestinal tumors, albeit with different efficiencies. By assessing both the anterior and posterior regions of the midgut, we observed regional differences in ISC/EB proliferation and tumor formation upon mutagenesis. Surprisingly, high continuous expression of Cas9 in ISCs/EBs blocked age-dependent increase in ISCs/EBs proliferation and when combined with gRNAs targeting tumor suppressors, it prevented tumorigenesis. However, no such effects were seen when temporal parameters of Cas9 were adjusted to regulate its expression levels or with a genetically modified version, which expresses Cas9 at lower levels, suggesting that fine-tuning Cas9 expression is essential to avoid deleterious effects. Our findings suggest that modifications to Cas9 expression results in differences in editing efficiency and careful considerations are required when choosing reagents for CRISPR-Cas9 mutagenesis studies. In summary, Drosophila can serve as a powerful model for context-dependent CRISPR-Cas based perturbations and to test genome-editing systems in vivo.

Recombinant Inbred Mice as Models for Experimental Precision Medicine and Biology

Recombinant inbred rodents form immortal genome-types that can be resampled deeply at many stages, in both sexes, and under multiple experimental conditions to model genome-environment interactions and to test genome-phenome predictions. This allows for experimental precision medicine, for which sophisticated causal models of complex interactions among DNA variants, phenotype variants at many levels, and innumerable environmental factors are required. Large families and populations of isogenic lines of mice and rats are now available and have been used across fields of biology. We will use the BXD recombinant inbred family and their derived diallel cross population as an example for predictive, experimental precision medicine and biology.

Application of Genome Sequencing from Blood to Diagnose Mitochondrial Diseases

Mitochondrial diseases can be caused by pathogenic variants in nuclear or mitochondrial DNA-encoded genes that often lead to multisystemic symptoms and can have any mode of inheritance. Using a single test, Genome Sequencing (GS) can effectively identify variants in both genomes, but it has not yet been universally used as a first-line approach to diagnosing mitochondrial diseases due to related costs and challenges in data analysis. In this article, we report three patients with mitochondrial disease molecularly diagnosed through GS performed on DNA extracted from blood to demonstrate different diagnostic advantages of this technology, including the detection of a low-level heteroplasmic pathogenic variant, an intragenic nuclear DNA deletion, and a large mtDNA deletion. Current technical improvements and cost reductions are likely to lead to an expanded routine diagnostic usage of GS and of the complementary “Omic” technologies in mitochondrial diseases.

Metabolic versatility of the nitrite-oxidizing bacterium Nitrospira marina and its proteomic response to oxygen-limited conditions

The genus Nitrospira is the most widespread group of nitrite-oxidizing bacteria and thrives in diverse natural and engineered ecosystems. Nitrospira marina Nb-295T was isolated from the ocean over 30 years ago; however, its genome has not yet been analyzed. Here, we investigated the metabolic potential of N. marina based on its complete genome sequence and performed physiological experiments to test genome-derived hypotheses. Our data confirm that N. marina benefits from additions of undefined organic carbon substrates, has adaptations to resist oxidative, osmotic, and UV light-induced stress and low dissolved pCO2, and requires exogenous vitamin B12. In addition, N. marina is able to grow chemoorganotrophically on formate, and is thus not an obligate chemolithoautotroph. We further investigated the proteomic response of N. marina to low (∼5.6 µM) O2 concentrations. The abundance of a potentially more efficient CO2-fixing pyruvate:ferredoxin oxidoreductase (POR) complex and a high-affinity cbb3-type terminal oxidase increased under O2 limitation, suggesting a role in sustaining nitrite oxidation-driven autotrophy. This putatively more O2-sensitive POR complex might be protected from oxidative damage by Cu/Zn-binding superoxide dismutase, which also increased in abundance under low O2 conditions. Furthermore, the upregulation of proteins involved in alternative energy metabolisms, including Group 3b [NiFe] hydrogenase and formate dehydrogenase, indicate a high metabolic versatility to survive conditions unfavorable for aerobic nitrite oxidation. In summary, the genome and proteome of the first marine Nitrospira isolate identifies adaptations to life in the oxic ocean and provides insights into the metabolic diversity and niche differentiation of NOB in marine environments.

Metabolic versatility of the nitrite-oxidizing bacterium Nitrospira marina and its proteomic response to oxygen-limited conditions

The genus Nitrospira is the most widespread group of chemolithoautotrophic nitrite-oxidizing bacteria that thrive in diverse natural and engineered ecosystems. Nitrospira marina Nb-295T represents the type genus and was isolated from the oceanic water column over 30 years ago, however, its genome has not yet been analyzed. Here, we analyzed the complete genome sequence of N. marina and performed select physiological experiments to test genome-derived hypotheses. Our data confirm that N. marina benefits from additions of undefined organic carbon substrates, has adaptations to combat oxidative, osmotic and UV-light induced stress and low dissolved pCO2, and is able to grow chemoorganotrophically on formate. We further investigated the metabolic response of N. marina to low (∼5.6 µM) O2 concentrations commonly encountered in marine environments with high nitrite concentrations. In response to O2-limited conditions, the abundance of a potentially more efficient CO2-fixing pyruvate:ferredoxin oxidoreductase (POR) complex and a high affinity cbb3-type terminal oxidase increased, suggesting a role in sustaining nitrite oxidation-driven autotrophy under O2 limitation. Additionally, a Cu/Zn-binding superoxide dismutase increased in abundance potentially protecting this putatively more O2-sensitive POR complex from oxidative damage. An increase in abundance of proteins involved in alternative energy metabolisms, including type 3b [NiFe] hydrogenase and formate dehydrogenase, indicate a high metabolic versatility to survive conditions unfavorable for aerobic nitrite oxidation. In summary, the genome and proteome of the first marine Nitrospira isolate identifies adaptations to life in the oxic ocean and provides important insights into the metabolic diversity and niche differentiation of NOB in marine environments.

Using Ancient Samples in Projection Analysis

Projection analysis is a useful tool for understanding the relationship of two populations. It compares a test genome to a set of genomes from a reference population. The projection's shape depends on the historical relationship of the test genome's population to the reference population. Here, we explore the effects on the projection when ancient samples are included in the analysis. First, we conduct a series of simulations in which the ancient sample is directly ancestral to a present-day population (one-population model) or the ancient sample is ancestral to a sister population that diverged before the time of sampling (two-population model). We find that there are characteristic differences between the projections for the one-population and two-population models, which indicate that the projection can be used to determine whether a test genome is directly ancestral to a present day population or not. Second, we compute projections for several published ancient genomes. We compare three Neanderthals, the Denisovan and three ancient human genomes to European, Han Chinese and Yoruba reference panels. We use a previously constructed demographic model and insert these seven ancient genomes and assess how well the observed projections are recovered.

The projection of a test genome onto a reference population and applications to humans and archaic hominins

We introduce a method for comparing a test genome with numerous genomes from a reference population. Sites in the test genome are given a weight w that depends on the allele frequency x in the reference population. The projection of the test genome onto the reference population is the average weight for each x, w(x). The weight is assigned in such a way that if the test genome is a random sample from the reference population, w(x)=1. Using analytic theory, numerical analysis, and simulations, we show how the projection depends on the time of population splitting, the history of admixture and changes in past population size. The projection is sensitive to small amounts of past admixture, the direction of admixture and admixture from a population not sampled (a ghost population). We compute the projection of several human and two archaic genomes onto three reference populations from the 1000 Genomes project, Europeans (CEU), Han Chinese (CHB) and Yoruba (YRI) and discuss the consistency of our analysis with previously published results for European and Yoruba demographic history. Including higher amounts of admixture between Europeans and Yoruba soon after their separation and low amounts of admixture more recently can resolve discrepancies between the projections and demographic inferences from some previous studies.