Biology subjects

Beisel, C.

Publications and source records attributed to Beisel, C..

42 records · Page 3Linked to original sources

bioRxiv2018

Distinct timescales of RNA regulators enable the construction of a genetic pulse generator

To build complex genetic networks with predictable behaviours, synthetic biologists use libraries of modular parts that can be characterized in isolation and assembled together to create programmable higher-order functions. Characterization experiments and computational models for gene regulatory parts operating in isolation are routinely employed to predict the dynamics of interconnected parts and guide the construction of new synthetic devices. Here, we individually characterize two modes of RNA-based transcriptional regulation, using small transcription activating RNAs (STARs) and CRISPR interference (CRISPRi), and show how their distinct regulatory timescales can be used to engineer a composed feedforward loop that creates a pulse of gene expression. We use a cell-free transcription-translation system (TXTL) to rapidly characterize the system, and we apply Bayesian inference to extract kinetic parameters for an ODE-based mechanistic model. We then demonstrate in simulation and verify with TXTL experiments that the simultaneous regulation of a single gene target with STARs and CRISPRi leads to a pulse of gene expression. Our results suggest the modularity of the two regulators in an integrated genetic circuit, and we anticipate that construction and modeling frameworks that can leverage this modularity will become increasingly important as synthetic circuits increase in complexity.

synthetic biology↗

bioRxiv2018

Intra-tumor heterogeneity and clonal exclusivity in renal cell carcinoma

Intra-tumour heterogeneity is the molecular hallmark of renal cancer, and the molecular tumour composition determines the treatment outcome of renal cancer patients. In renal cancer tumourigenesis, in general, different tumour clones evolve over time. We analysed intra-tumour heterogeneity and subclonal mutation patterns in 178 tumour samples obtained from 89 clear cell renal cell carcinoma patients. In an initial discovery phase, whole-exome and transcriptome sequencing data from paired tumour biopsies from 16 ccRCC patients were used to design a gene panel for follow-up analysis. In this second phase, 826 selected genes were targeted at deep coverage in an extended cohort of 89 patients for a detailed analysis of tumour heterogeneity. On average, we found 22 mutations per patient. Pairwise comparison of the two biopsies from the same tumour revealed that on average 62% of the mutations in a patient were detected in one of the two samples. In addition to commonly mutated genes (VHL, PBRM1, SETD2 and BAP1), frequent subclonal mutations with low variant allele frequency (<10%) were observed in TP53 and in mucin coding genes MUC6, MUC16, and MUC3A. Of the 89 ccRCC tumours, 87 (~98%) harboured private mutations, occurring in only one of the paired tumour samples. Clonally exclusive pathway pairs were identified using the WES data set from 16 ccRCC patients. Our findings imply that shared and private mutations significantly contribute to the complexity of differential gene expression and pathway interaction, and might explain clonal evolution of different molecular renal cancer subgroups. Multi-regional sequencing is central for the identification of subclones within ccRCC.

cancer biology↗

bioRxiv2018

Treemmer: a tool to reduce large phylogenetic datasets with minimal loss of diversity

Large sequence datasets are difficult to visualize and handle. Additionally, they are often not an adequate representation of the natural diversity, but the result of uncoordinated and convenience sampling. Consequently, they can suffer from redundancy and sampling biases. Here we present Treemmer, a simple tool to evaluate the redundancy of phylogenetic trees and reduce their complexity by eliminating leaves that contribute the least to the tree diversity.\n\nTreemmer can reduce the size of datasets with different phylogenetic structures and levels of redundancy while maintaining a sub-sample that is representative of the original diversity.

bioinformatics↗

bioRxiv2017

Bacterial adaptation to host diet is a key evolutionary force shaping host-microbe symbiosis

Life on Earth was dominated by bacteria for billions of years1. About 600 million years ago, animal life emerged and micro-organisms played a crucial role in shaping animal development, physiology and evolution2-4. The two partners committed to a symbiotic relationship that persists in nearly all animals today. Such beneficial interactions are pervasive throughout nature and have been extensively characterized5,6. However, the ecological and evolutionary forces that drive the emergence and evolution of the symbiont benefits to their animal hosts remain largely elusive. Here we show that the host nutritional environment, instead of the host, is a predominant driving force in this evolutionary process and we identify a mechanism resulting from the bacterial adaptation to the diet, which confers improved functional benefit to the host. By applying experimental evolution to a model of host-bacteria beneficial symbiosis: Drosophila melanogaster associated with Lactobacillus plantarum, one of its growth promoting symbiotic bacteria7,8, we found that the de novo mutations in the same acetate kinase (ackA) locus invariably emerge first, rapidly become fixed, and such evolution occurs with or without the host. Furthermore, we demonstrate that ackA mutations trigger the increased production of N-acetyl-glutamine, which is sufficient to confer improved host growth capabilities to the evolved bacterial strains. Our study therefore identifies a specific mechanism by which a symbiotic bacterium increases its benefit to its animal host and reveals that adaptation to the host diet is a foremost step in the determination of the evolutionary course of symbiosis between an animal and its gut microbes.

evolutionary biology↗

bioRxiv2017

Comparative genomics of Mycobacterium africanum Lineage 5 and Lineage 6 from Ghana suggests different ecological niches

Mycobacterium africanum (Maf) causes up to half of human tuberculosis in West Africa, but little is known on this pathogen. We compared the genomes of 253 Maf clinical isolates from Ghana, including both L5 and L6. We found that the genomic diversity of L6 was higher than in L5, and the selection pressures differed between both groups. Regulatory proteins appeared to evolve neutrally in L5 but under purifying selection in L6. Conversely, human T cell epitopes were under purifying selection in L5, but under positive selection in L6. Although only 10% of the T cell epitopes were variable, mutations were mostly lineage-specific. Our findings indicate that Maf L5 and L6 are genomically distinct, possibly reflecting different ecological niches.

genomics↗

bioRxiv2017

Rapid and scalable characterization of CRISPR technologies using an E. coli cell-free transcription-translation system

CRISPR-Cas systems have offered versatile technologies for genome engineering, yet their implementation has been outpaced by the ongoing discovery of new Cas nucleases and anti-CRISPR proteins. Here, we present the use of E. coli cell-free transcription-translation systems (TXTL) to vastly improve the speed and scalability of CRISPR characterization and validation. Unlike prior approaches that require protein purification or live cells, TXTL can express active CRISPR machinery from added plasmids and linear DNA, and TXTL can output quantitative dynamics of DNA cleavage and gene repression. To demonstrate the applicability of TXTL, we rapidly measure guide RNA-dependent DNA cleavage and gene repression for single- and multi-effector CRISPR-Cas systems, accurately predict the strength of gene repression in E. coli, quantify the inhibitory activity of anti-CRISPR proteins, and develop a fast and scalable high-throughput screen for protospacer-adjacent motifs. These examples underscore the potential of TXTL to facilitate the characterization and application of CRISPR technologies across their many uses.

synthetic biology↗