Whole-genome sequence of the plant-associated bacterium Pseudomonas granadensis CT364 isolated in Seville, Spain.

Pseudomonas sp. CT364 was isolated from olive tree rhizosphere in Seville (Spain). We report its complete genome sequence, acquired by co-assembling Illumina and Nanopore reads. The genome comprises a circular chromosome of 6.2 Mbp and a G + C content of 60.0%. Taxonomic analyses confirmed it to be Pseudomonas granadensis.

Mottle: Accurate pairwise substitution distance at high divergence through the exploitation of short-read mappers and gradient descent.

Current tools for estimating the substitution distance between two related sequences struggle to remain accurate at a high divergence. Difficulties at distant homologies, such as false seeding and over-alignment, create a high barrier for the development of a stable estimator. This is especially true for viral genomes, which carry a high rate of mutation, small size, and sparse taxonomy. Developing an accurate substitution distance measure would help to elucidate the relationship between highly divergent sequences, interrogate their evolutionary history, and better facilitate the discovery of new viral genomes. To tackle these problems, we propose an approach that uses short-read mappers to create whole-genome maps, and gradient descent to isolate the homologous fraction and calculate the final distance value. We implement this approach as Mottle. With the use of simulated and biological sequences, Mottle was able to remain stable to 0.66-0.96 substitutions per base pair and identify viral outgroup genomes with 95% accuracy at the family-order level. Our results indicate that Mottle performs as well as existing programs in identifying taxonomic relationships, with more accurate numerical estimation of genomic distance over greater divergences. By contrast, one limitation is a reduced numerical accuracy at low divergences, and on genomes where insertions and deletions are uncommon, when compared to alternative approaches. We propose that Mottle may therefore be of particular interest in the study of viruses, viral relationships, and notably for viral discovery platforms, helping in benchmarking of homology search tools and defining the limits of taxonomic classification methods. The code for Mottle is available at https://github.com/tphoward/Mottle_Repo.

Evolving Role of Proton Radiation Therapy in Clinical Practice.

With the expansion of proton radiation therapy centers across the United States and a gradually expanding body of academic evidence supporting its use, more patients are receiving-and asking about-proton therapy than ever before. Here, we outline, for nonradiation oncologists, the theoretical benefits of proton therapy, the clinical evidence to date, the controversies affecting utilization, and the numerous randomized trials currently in progress. We also discuss the challenges of researching and delivering proton therapy, including the cost of constructing and maintaining centers, barriers with insurance approval, clinical situations in which proton therapy may be approached with caution, and the issue of equitable access for all patients. The purpose of this review is to assist practicing oncologists in understanding the evolving role of proton therapy and to help nonradiation oncologists guide patients regarding this technology.

Methods for Embedding Cell-Free Protein Synthesis Reactions in Macro-Scale Hydrogels.

Synthetic gene networks provide a platform for scientists and engineers to design and build novel systems with functionality encoded at a genetic level. While the dominant paradigm for the deployment of gene networks is within a cellular chassis, synthetic gene networks may also be deployed in cell-free environments. Promising applications of cell-free gene networks include biosensors, as these devices have been demonstrated against biotic (Ebola, Zika, and SARS-CoV-2 viruses) and abiotic (heavy metals, sulfides, pesticides, and other organic contaminants) targets. Cell-free systems are typically deployed in liquid form within a reaction vessel. Being able to embed such reactions in a physical matrix, however, may facilitate their broader application in a wider set of environments. To this end, methods for embedding cell-free protein synthesis (CFPS) reactions in a variety of hydrogel matrices have been developed. One of the key properties of hydrogels conducive to this work is the high-water reconstitution capacity of hydrogel materials. Additionally, hydrogels possess physical and chemical characteristics that are functionally beneficial. Hydrogels can be freeze-dried for storage and rehydrated for use later. Two step-by-step protocols for the inclusion and assay of CFPS reactions in hydrogels are presented. First, a CFPS system can be incorporated into a hydrogel via rehydration with a cell lysate. The system within the hydrogel can then be induced or expressed constitutively for complete protein expression through the hydrogel. Second, cell lysate can be introduced to a hydrogel at the point of polymerization, and the entire system can be freeze-dried and rehydrated at a later point with an aqueous solution containing the inducer for the expression system encoded within the hydrogel. These methods have the potential to allow for cell-free gene networks that confer sensory capabilities to hydrogel materials, with the potential for deployment beyond the laboratory.

Key reaction components affect the kinetics and performance robustness of cell-free protein synthesis reactions.

Cell-free protein synthesis (CFPS) reactions have grown in popularity with particular interest in applications such as gene construct prototyping, biosensor technologies and the production of proteins with novel chemistry. Work has frequently focussed on optimising CFPS protocols for improving protein yield, reducing cost, or developing streamlined production protocols. Here we describe a statistical Design of Experiments analysis of 20 components of a popular CFPS reaction buffer. We simultaneously identify factors and factor interactions that impact on protein yield, rate of reaction, lag time and reaction longevity. This systematic experimental approach enables the creation of a statistical model capturing multiple behaviours of CFPS reactions in response to components and their interactions. We show that a novel reaction buffer outperforms the reference reaction by 400% and importantly reduces failures in CFPS across batches of cell lysates, strains of E. coli, and in the synthesis of different proteins. Detailed and quantitative understanding of how reaction components affect kinetic responses and robustness is imperative for future deployment of cell-free technologies.

Clinical outcomes for pediatric patients receiving radiotherapy for solid tumor central nervous system metastases.

Central nervous system (CNS) metastases are rare, but devastating complications of pediatric solid tumors. Radiotherapy alone or postresection serves as an important treatment; however, data on the use of whole-brain radiotherapy (WBRT) versus focal radiotherapy, including stereotactic radiosurgery or stereotactic radiotherapy, for these indications are limited. We report a single institution experience of 26 pediatric patients treated with radiotherapy for solid tumor CNS metastases without leptomeningeal disease. Focal radiotherapy (n = 10) was well tolerated and survival outcomes did not differ between patients treated with WBRT (n = 16) versus focal radiation, suggesting that focal radiotherapy may be considered for patients with limited CNS metastases.

pCAT vectors overcome inefficient electroporation of Cupriavidus necator H16.

Cupriavidus necator H16 is a chemolithoautotroph with a range of industrial biotechnological applications. Advanced metabolic engineering in the bacterium, however, is impeded by low transformation efficiency, making it difficult to introduce and screen new genetic functions rapidly. This study systematically characterized the broad host range plasmids pBHR1, pBBR1MCS-2 and pKT230 used frequently for C. necator engineering. Kanamycin resistance cassette (KanR) and a truncated sequence of the replication origin (Rep) are contributing factors to C. necator low electroporation transformation efficiency. Consequently, a series of modular minimal plasmids, named pCAT, were constructed. pCAT vectors transform C. necator H16 with a > 3000-fold higher efficiency (up to 107 CFU/µg DNA) compared to control plasmids. Further, pCAT vectors are highly stable, expressing reporter proteins over several days of serial cultivation in the absence of selection pressure. Finally, they can be assembled rapidly from PCR or synthesized DNA fragments, and restriction-ligation reactions can be efficiently electroporated directly into C. necator, circumventing the requirement to use Escherichia coli for plasmid maintenance or propagation. This study demonstrates that an understanding of the behaviour of the constituent parts of plasmids in a host is key to efficient propagation of genetic information, while offering new methods for engineering a bacterium with desirable industrial biotechnological features.

Haplotype-resolved germline and somatic alterations in renal medullary carcinomas.

BACKGROUND: Renal medullary carcinomas (RMCs) are rare kidney cancers that occur in adolescents and young adults of African ancestry. Although RMC is associated with the sickle cell trait and somatic loss of the tumor suppressor, SMARCB1, the ancestral origins of RMC remain unknown. Further, characterization of structural variants (SVs) involving SMARCB1 in RMC remains limited. METHODS: We used linked-read genome sequencing to reconstruct germline and somatic haplotypes in 15 unrelated patients with RMC registered on the Children's Oncology Group (COG) AREN03B2 study between 2006 and 2017 or from our prior study. We performed fine-mapping of the HBB locus and assessed the germline for cancer predisposition genes. Subsequently, we assessed the tumor samples for mutations outside of SMARCB1 and integrated RNA sequencing to interrogate the structural variants at the SMARCB1 locus. RESULTS: We find that the haplotype of the sickle cell mutation in patients with RMC originated from three geographical regions in Africa. In addition, fine-mapping of the HBB locus identified the sickle cell mutation as the sole candidate variant. We further identify that the SMARCB1 structural variants are characterized by blunt or 1-bp homology events. CONCLUSIONS: Our findings suggest that RMC does not arise from a single founder population and that the HbS allele is a strong candidate germline allele which confers risk for RMC. Furthermore, we find that the SVs that disrupt SMARCB1 function are likely repaired by non-homologous end-joining. These findings highlight how haplotype-based analyses using linked-read genome sequencing can be applied to identify potential risk variants in small and rare disease cohorts and provide nucleotide resolution to structural variants.

A first-generation pediatric cancer dependency map.

Exciting therapeutic targets are emerging from CRISPR-based screens of high mutational-burden adult cancers. A key question, however, is whether functional genomic approaches will yield new targets in pediatric cancers, known for remarkably few mutations, which often encode proteins considered challenging drug targets. To address this, we created a first-generation pediatric cancer dependency map representing 13 pediatric solid and brain tumor types. Eighty-two pediatric cancer cell lines were subjected to genome-scale CRISPR-Cas9 loss-of-function screening to identify genes required for cell survival. In contrast to the finding that pediatric cancers harbor fewer somatic mutations, we found a similar complexity of genetic dependencies in pediatric cancer cell lines compared to that in adult models. Findings from the pediatric cancer dependency map provide preclinical support for ongoing precision medicine clinical trials. The vulnerabilities observed in pediatric cancers were often distinct from those in adult cancer, indicating that repurposing adult oncology drugs will be insufficient to address childhood cancers.

Plant pest surveillance: from satellites to molecules.

Plant pests and diseases impact both food security and natural ecosystems, and the impact has been accelerated in recent years due to several confounding factors. The globalisation of trade has moved pests out of natural ranges, creating damaging epidemics in new regions. Climate change has extended the range of pests and the pathogens they vector. Resistance to agrochemicals has made pathogens, pests, and weeds more difficult to control. Early detection is critical to achieve effective control, both from a biosecurity as well as an endemic pest perspective. Molecular diagnostics has revolutionised our ability to identify pests and diseases over the past two decades, but more recent technological innovations are enabling us to achieve better pest surveillance. In this review, we will explore the different technologies that are enabling this advancing capability and discuss the drivers that will shape its future deployment.

Partitioning of Chemotherapeutics into Nuclear Condensates-Opening the Door to New Approaches for Drug Development.

Klein et al. (2020) demonstrate for the first time that small-molecule cancer therapeutics are selectively partitioned and concentrated within phase-separated nuclear condensates, providing new insights to drug efficacy and creating the opportunity for enhanced control of therapeutic targeting.

Rhabdoid Tumors Are Sensitive to the Protein-Translation Inhibitor Homoharringtonine.

PURPOSE: Rhabdoid tumors are devastating pediatric cancers in need of improved therapies. We sought to identify small molecules that exhibit in vitro and in vivo efficacy against preclinical models of rhabdoid tumor. EXPERIMENTAL DESIGN: We screened eight rhabdoid tumor cell lines with 481 small molecules and compared their sensitivity with that of 879 other cancer cell lines. Genome-scale CRISPR-Cas9 inactivation screens in rhabdoid tumors were analyzed to confirm target vulnerabilities. Gene expression and CRISPR-Cas9 data were queried across cell lines and primary rhabdoid tumors to discover biomarkers of small-molecule sensitivity. Molecular correlates were validated by manipulating gene expression. Subcutaneous rhabdoid tumor xenografts were treated with the most effective drug to confirm in vitro results. RESULTS: Small-molecule screening identified the protein-translation inhibitor homoharringtonine (HHT), an FDA-approved treatment for chronic myelogenous leukemia (CML), as the sole drug to which all rhabdoid tumor cell lines were selectively sensitive. Validation studies confirmed the sensitivity of rhabdoid tumor to HHT was comparable with that of CML cell lines. Low expression of the antiapoptotic gene BCL2L1, which encodes Bcl-XL, was the strongest predictor of HHT sensitivity, and HHT treatment consistently depleted Mcl-1, the synthetic-lethal antiapoptotic partner of Bcl-XL. Rhabdoid tumor cell lines and primary-tumor samples expressed low BCL2L1, and overexpression of BCL2L1 induced resistance to HHT in rhabdoid tumor cells. Furthermore, HHT treatment inhibited rhabdoid tumor cell line and patient-derived xenograft growth in vivo. CONCLUSIONS: Rhabdoid tumor cell lines and xenografts are highly sensitive to HHT, at least partially due to their low expression of BCL2L1. HHT may have therapeutic potential against rhabdoid tumors.

Applying Statistical Design of Experiments To Understanding the Effect of Growth Medium Components on Cupriavidus necator H16 Growth.

Cupriavidus necator H16 is gaining significant attention as a microbial chassis for range of biotechnological applications. While the bacterium is a major producer of bioplastics, its lithoautotrophic and versatile metabolic capabilities make the bacterium a promising microbial chassis for biofuels and chemicals using renewable resources. It remains necessary to develop appropriate experimental resources to permit controlled bioengineering and system optimization of this microbe. In this study, we employed statistical design of experiments to gain understanding of the impact of components of defined media on C. necator growth and built a model that can predict the bacterium's cell density based on medium components. This highlighted medium components, and interaction between components, having the most effect on growth: fructose, amino acids, trace elements, CaCl2, and Na2HPO4 contributed significantly to growth (t values of <-1.65 or >1.65); copper and histidine were found to interact and must be balanced for robust growth. Our model was experimentally validated and found to correlate well (r2 = 0.85). Model validation at large culture scales showed correlations between our model-predicted growth ranks and experimentally determined ranks at 100 ml in shake flasks (ρ = 0.87) and 1 liter in a bioreactor (ρ = 0.90). Our approach provides valuable and quantifiable insights on the impact of medium components on cell growth and can be applied to model other C. necator responses that are crucial for its deployment as a microbial chassis. This approach can be extended to other nonmodel microbes of medical and industrial biotechnological importance.IMPORTANCE Chemically defined media (CDM) for cultivation of C. necator vary in components and compositions. This lack of consensus makes it difficult to optimize new processes for the bacterium. This study employed statistical design of experiments (DOE) to understand how basic components of defined media affect C. necator growth. Our growth model predicts that C. necator can be cultivated to high cell density with components held at low concentrations, arguing that CDM for large-scale cultivation of the bacterium for industrial purposes will be economically competitive. Although existing CDM for the bacterium are without amino acids, addition of a few amino acids to growth medium shortened lag phase of growth. The interactions highlighted by our growth model show how factors can interact with each other during a process to positively or negatively affect process output. This approach is efficient, relying on few well-structured experimental runs to gain maximum information on a biological process, growth.

Cell-free protein synthesis in hydrogel materials.

We report a method for embedding cell-free protein synthesis reactions in macro-scale hydrogel materials without a free liquid phase. This paper focuses on methods of preparation for a variety of hydrogels and an investigation of the impact that the hydrogel material has on cell-free protein synthesis.

Author Correction: BRD9 defines a SWI/SNF sub-complex and constitutes a specific vulnerability in malignant rhabdoid tumors.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Rapid, Heuristic Discovery and Design of Promoter Collections in Non-Model Microbes for Industrial Applications.

Well-characterized promoter collections for synthetic biology applications are not always available in industrially relevant hosts. We developed a broadly applicable method for promoter identification in atypical microbial hosts that requires no a priori understanding of cis-regulatory element structure. This novel approach combines bioinformatic filtering with rapid empirical characterization to expand the promoter toolkit and uses machine learning to improve the understanding of the relationship between DNA sequence and function. Here, we apply the method in Geobacillus thermoglucosidasius, a thermophilic organism with high potential as a synthetic biology chassis for industrial applications. Bioinformatic screening of G. kaustophilus, G. stearothermophilus, G. thermodenitrificans, and G. thermoglucosidasius resulted in the identification of 636 100 bp putative promoters, encompassing the genome-wide design space and lacking known transcription factor binding sites. Eighty of these sequences were characterized in vivo, and activities covered a 2-log range of predictable expression levels. Seven sequences were shown to function consistently regardless of the downstream coding sequence. Partition modeling identified sequence positions upstream of the canonical -35 and -10 consensus motifs that were predicted to strongly influence regulatory activity in Geobacillus, and artificial neural network and partial least squares regression models were derived to assess if there were a simple, forward, quantitative method for in silico prediction of promoter function. However, the models were insufficiently general to predict pre hoc promoter activity in vivo, most probably as a result of the relatively small size of the training data set compared to the size of the modeled design space.

BRD9 defines a SWI/SNF sub-complex and constitutes a specific vulnerability in malignant rhabdoid tumors.

Bromodomain-containing protein 9 (BRD9) is a recently identified subunit of SWI/SNF(BAF) chromatin remodeling complexes, yet its function is poorly understood. Here, using a genome-wide CRISPR-Cas9 screen, we show that BRD9 is a specific vulnerability in pediatric malignant rhabdoid tumors (RTs), which are driven by inactivation of the SMARCB1 subunit of SWI/SNF. We find that BRD9 exists in a unique SWI/SNF sub-complex that lacks SMARCB1, which has been considered a core subunit. While SMARCB1-containing SWI/SNF complexes are bound preferentially at enhancers, we show that BRD9-containing complexes exist at both promoters and enhancers. Mechanistically, we show that SMARCB1 loss causes increased BRD9 incorporation into SWI/SNF thus providing insight into BRD9 vulnerability in RTs. Underlying the dependency, while its bromodomain is dispensable, the DUF3512 domain of BRD9 is essential for SWI/SNF integrity in the absence of SMARCB1. Collectively, our results reveal a BRD9-containing SWI/SNF subcomplex is required for the survival of SMARCB1-mutant RTs.

Renal medullary carcinomas depend upon SMARCB1 loss and are sensitive to proteasome inhibition.

Renal medullary carcinoma (RMC) is a rare and deadly kidney cancer in patients of African descent with sickle cell trait. We have developed faithful patient-derived RMC models and using whole-genome sequencing, we identified loss-of-function intronic fusion events in one SMARCB1 allele with concurrent loss of the other allele. Biochemical and functional characterization of these models revealed that RMC requires the loss of SMARCB1 for survival. Through integration of RNAi and CRISPR-Cas9 loss-of-function genetic screens and a small-molecule screen, we found that the ubiquitin-proteasome system (UPS) was essential in RMC. Inhibition of the UPS caused a G2/M arrest due to constitutive accumulation of cyclin B1. These observations extend across cancers that harbor SMARCB1 loss, which also require expression of the E2 ubiquitin-conjugating enzyme, UBE2C. Our studies identify a synthetic lethal relationship between SMARCB1-deficient cancers and reliance on the UPS which provides the foundation for a mechanism-informed clinical trial with proteasome inhibitors.

MDM2 and MDM4 Are Therapeutic Vulnerabilities in Malignant Rhabdoid Tumors.

Malignant rhabdoid tumors (MRT) are highly aggressive pediatric cancers that respond poorly to current therapies. In this study, we screened several MRT cell lines with large-scale RNAi, CRISPR-Cas9, and small-molecule libraries to identify potential drug targets specific for these cancers. We discovered MDM2 and MDM4, the canonical negative regulators of p53, as significant vulnerabilities. Using two compounds currently in clinical development, idasanutlin (MDM2-specific) and ATSP-7041 (MDM2/4-dual), we show that MRT cells were more sensitive than other p53 wild-type cancer cell lines to inhibition of MDM2 alone as well as dual inhibition of MDM2/4. These compounds caused significant upregulation of the p53 pathway in MRT cells, and sensitivity was ablated by CRISPR-Cas9-mediated inactivation of TP53. We show that loss of SMARCB1, a subunit of the SWI/SNF (BAF) complex mutated in nearly all MRTs, sensitized cells to MDM2 and MDM2/4 inhibition by enhancing p53-mediated apoptosis. Both MDM2 and MDM2/4 inhibition slowed MRT xenograft growth in vivo, with a 5-day idasanutlin pulse causing marked regression of all xenografts, including durable complete responses in 50% of mice. Together, these studies identify a genetic connection between mutations in the SWI/SNF chromatin-remodeling complex and the tumor suppressor gene TP53 and provide preclinical evidence to support the targeting of MDM2 and MDM4 in this often-fatal pediatric cancer. SIGNIFICANCE: This study identifies two targets, MDM2 and MDM4, as vulnerabilities in a deadly pediatric cancer and provides preclinical evidence that compounds inhibiting these proteins have therapeutic potential.

Mutational processes shape the landscape of TP53 mutations in human cancer.

Unlike most tumor suppressor genes, the most common genetic alterations in tumor protein p53 (TP53) are missense mutations1,2. Mutant p53 protein is often abundantly expressed in cancers and specific allelic variants exhibit dominant-negative or gain-of-function activities in experimental models3-8. To gain a systematic view of p53 function, we interrogated loss-of-function screens conducted in hundreds of human cancer cell lines and performed TP53 saturation mutagenesis screens in an isogenic pair of TP53 wild-type and null cell lines. We found that loss or dominant-negative inhibition of wild-type p53 function reliably enhanced cellular fitness. By integrating these data with the Catalog of Somatic Mutations in Cancer (COSMIC) mutational signatures database9,10, we developed a statistical model that describes the TP53 mutational spectrum as a function of the baseline probability of acquiring each mutation and the fitness advantage conferred by attenuation of p53 activity. Collectively, these observations show that widely-acting and tissue-specific mutational processes combine with phenotypic selection to dictate the frequencies of recurrent TP53 mutations.