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Beisel, C.

Publications and source records attributed to Beisel, C..

At least 37 records · Page 2Linked to original sources

Temporal and sequential transcriptional dynamics define lineage shifts in corticogenesis

The cerebral cortex contains billions of neurons, and their disorganization or misspecification leads to neurodevelopmental disorders. Understanding how the plethora of projection neuron subtypes are generated by cortical neural stem cells (NSCs) is a major challenge. Here, we focused on elucidating the transcriptional landscape of murine embryonic NSCs, basal progenitors (BPs) and newborn neurons (NBNs) throughout cortical development. We uncover dynamic shifts in transcriptional space over time, and heterogeneity within each progenitor population. We identified signature hallmarks of NSC, BP and NBN clusters, and predict active transcriptional nodes and networks that contribute to neural fate specification. We find that the expression of receptors, ligands and downstream pathway components is highly dynamic over time and throughout the lineage implying differential responsiveness to signals. Thus, we provide an expansive compendium of gene expression during cortical development that will be an invaluable resource for studying neural developmental processes and neurodevelopmental disorders.

neuroscience↗

Differentially optimized cell-free buffer enables robust expression from unprotected linear DNA in exonuclease-deficient extracts

The use of linear DNA templates in cell-free systems promises to accelerate the prototyping and engineering of synthetic gene circuits. A key challenge is that linear templates are rapidly degraded by exonucleases present in cell extracts. Current approaches tackle the problem by adding exonuclease inhibitors and DNA-binding proteins to protect the linear DNA, requiring additional time- and resource-intensive steps. Here, we delete the recBCD exonuclease gene cluster from the Escherichia coli BL21 genome. We show that the resulting cell-free systems, with buffers optimized specifically for linear DNA, enable near-plasmid levels of expression from {sigma}70 promoters in linear DNA templates without employing additional protection strategies. When using linear or plasmid DNA templates at the buffer calibration step, the optimal potassium glutamate concentrations obtained when using linear DNA were consistently lower than those obtained when using plasmid DNA for the same extract. We demonstrate the robustness of the exonuclease deficient extracts across seven different batches and a wide range of experimental conditions across two different laboratories. Finally, we illustrate the use of the {Delta}recBCD extracts for two applications: toehold switch characterization and enzyme screening. Our work provides a simple, efficient, and cost-effective solution for using linear DNA templates in cell-free systems and highlights the importance of specifically tailoring buffer composition for the final experimental setup. Our data also suggest that similar exonuclease deletion strategies can be applied to other species suitable for cell-free synthetic biology.

synthetic biology↗

Beneficial Lactiplantibacillus plantarum promote Drosophila growth by down-regulating the expression of PGRP-SC1

Animals and their commensal bacteria are known to reciprocally influence many traits of their physiology. Specifically, microbes contribute to the maintenance of the immune system homeostasis, improve host digestive processes, and sustain host growth and development. Several studies have reported that such effects result from an intricate network of nutritional, metabolic and immune inputs and partly rely on the capacity of microbes to regulate the hosts transcriptional response. However, these evidences mainly come from comparing the transcriptional response caused by commensal bacteria with that of axenic animals, making it difficult to identify the specific animal genes that are regulated by beneficial microbes. Here, we employ a well-established model of nutritional symbiosis, Drosophila melanogaster associated with Lactiplantibacillus plantarum, to understand the host genetic pathways regulated by beneficial bacteria and leading to improved host growth and development. Using isogenic L. plantarum strains bearing different growth-promoting effects, we show that the microbial benefit to the host relies on the down-regulation of peptidoglycan- recognition proteins. In particular, we report that the lower expression of PGRP-SC1 exerted by growth-promoting bacteria is responsible for their higher proliferation and the consequent increased production of beneficial metabolites, which ultimately leads to improved host growth and development. Our study helps elucidate the mechanisms underlying the beneficial effect exerted by commensal bacteria, defining the role of PGRP-SC1 in the relationship between Drosophila and its gut microbes. IMPORTANCECommensal bacteria are in constant association with their animal hosts, significantly affecting animal physiology through an intricate network of nutritional, metabolic and immune inputs. Yet, how beneficial bacteria specifically improve animal health is not fully understood. Here, we used a well-established model of nutritional symbiosis to understand how beneficial gut microbes improve host growth via regulation of its transcriptional response. Our study advances the current knowledge in host-microbe interactions by demonstrating that commensal bacteria improve fly growth by actively regulating the expression of immune effectors, which lead to higher immune tolerance. This leads to higher bacterial proliferation and the increased production of beneficial microbial metabolites, which are then consumed by the host. Our results shed light on the complex mechanisms underlying the relationships between a host and its gut microbes.

microbiology↗

A statistical test for clonal exclusivity in tumour evolution

Tumour progression is an evolutionary process in which different clones evolve over time, leading to intra-tumour heterogeneity. Interactions between clones can affect tumour evolution and hence disease progression and treatment outcome. Pairs of mutations that are overrepresented in a clonally exclusive fashion over a cohort of patient samples may be suggestive of a synergistic effect between the different clones carrying these mutations. We therefore developed a novel statistical test, called GeneAccord, to identify such gene pairs that are altered in distinct subclones of the same tumour. We analysed our test for calibration and power. By comparing its performance to baseline methods, we demonstrate that to control type I errors, it is essential to account for the evolutionary dependencies among clones. In applying GeneAccord to the single-cell sequencing of a cohort of 123 acute myeloid leukaemia patients, we find 6 clonally exclusive and 2 clonally co-occurring gene pairs. The clonally exclusive pairs mostly involve genes of the key signalling pathways.

cancer biology↗

Large-scale phylogenomics of the genus Macrostomum (Platyhelminthes) reveals cryptic diversity and novel sexual traits

Free-living flatworms of the genus Macrostomum are small and transparent animals, representing attractive study organisms for a broad range of topics in evolutionary, developmental, and molecular biology. The genus includes the model organism M. lignano for which extensive molecular resources are available, and recently there is a growing interest in extending work to additional species in the genus. These endeavours are currently hindered because, even though >200 Macrostomum species have been taxonomically described, molecular phylogenetic information and geographic sampling remain limited. We report on a global sampling campaign aimed at increasing taxon sampling and geographic representation of the genus. Specifically, we use extensive transcriptome and single-locus data to generate phylogenomic hypotheses including 145 species. Across different phylogenetic methods and alignments used, we identify several consistent clades, while their exact grouping is less clear, possibly due to a radiation early in Macrostomum evolution. Moreover, we uncover a large undescribed diversity, with 94 of the studied species likely being new to science, and we identify multiple novel morphological traits. Furthermore, we identify cryptic speciation in a taxonomically challenging assemblage of species, suggesting that the use of molecular markers is a prerequisite for future work, and we describe the distribution of possible synapomorphies and suggest taxonomic revisions based on our finding. Our large-scale phylogenomic dataset now provides a robust foundation for comparative analyses of morphological, behavioural and molecular evolution in this genus.

evolutionary biology↗

Dynamic changes of genomic and transcriptomic tumor diversity during melanoma progression

Metastatic melanoma is an aggressive disease that is notoriously difficult to treat. Here, we used a BRAFV600E-driven mouse model to study melanoma progression and metastasis in the absence of extrinsic mutagenic factors such as UV radiation. The tumors were grown for different time periods in seven different mice such that disease progression was tracked over time. We sequenced the whole exome and whole transcriptome of 16 melanoma samples from these mice. The timed samples revealed that many genes are increasingly upregulated during progression, such as genes involved in extracellular matrix organization, and Vegfc, a factor that induces lymphatic vessel growth and metastases to lymph nodes, which was identified as an important signaling hub in our analysis. The Vegfc gene interaction network highlighted multiple genes from the MAPK pathway that are increasingly deregulated during tumor evolution. The genomic diversity of primary and metastatic tumors showed an increase over time. Additionally, our integrative multi-omics analysis adds further evidence that Rock1 is a crucial player driving metastasis formation, and may be upregulated due to mutations in the PI3K/AKT pathway. In summary, our study contributes towards an improved understanding of melanoma which may eventually lead to improved treatment strategies.

cancer biology↗

Frequent origins of traumatic insemination involve convergent shifts in sperm and genital morphology

Traumatic insemination is a mating behaviour during which the (sperm) donor uses a traumatic intromittent organ to inject an ejaculate through the epidermis of the (sperm) recipient, thereby frequently circumventing the female genitalia. Traumatic insemination occurs widely across animals, but the frequency of its evolution, the intermediate stages via which it originates, and the morphological changes that such shifts involve remain poorly understood. Based on observations in 145 species of the free-living flatworm genus Macrostomum, we identify at least nine independent evolutionary origins of traumatic insemination from reciprocal copulation, but no clear indication of reversals. These origins involve convergent shifts in multivariate morphospace of male and female reproductive traits, suggesting that traumatic insemination has a canalising effect on morphology. Signatures of male-female coevolution across the genus indicate that sexual selection and sexual conflict drive the evolution of traumatic insemination, because it allows donors to bypass postcopulatory control mechanisms of recipients.

evolutionary biology↗

Local adaptation in populations of Mycobacterium tuberculosis endemic to the Indian Ocean Rim

Lineage 1 (L1) and 3 (L3) are two lineages of the Mycobacterium tuberculosis complex (MTBC), causing tuberculosis (TB) in humans. L1 and L3 are endemic to the Rim of the Indian Ocean, the region that accounts for most of the worlds new TB cases. Despite their relevance for this region, L1 and L3 remain understudied. Here we analyzed 2,938 L1 and 2,030 L3 whole genome sequences originating from 69 countries. We show that South Asia played a central role in the dispersion of these two lineages to neighboring regions. Moreover, we found that L1 exhibits signatures of local adaptation at the esxH locus, a gene coding for a secreted effector that targets the human endosomal sorting complex, and is included in several vaccine candidates. Our study highlights the importance of genetic diversity in the MTBC, and sheds new light on two of the most important MTBC lineages affecting humans.

genomics↗

Within-patient genetic diversity of SARS-CoV-2

SARS-CoV-2, the virus responsible for the current COVID-19 pandemic, is evolving into different genetic variants by accumulating mutations as it spreads globally. In addition to this diversity of consensus genomes across patients, RNA viruses can also display genetic diversity within individual hosts, and co-existing viral variants may affect disease progression and the success of medical interventions. To systematically examine the intra-patient genetic diversity of SARS-CoV-2, we processed a large cohort of 3939 publicly-available deeply sequenced genomes with specialised bioinformatics software, along with 749 recently sequenced samples from Switzerland. We found that the distribution of diversity across patients and across genomic loci is very unbalanced with a minority of hosts and positions accounting for much of the diversity. For example, the D614G variant in the Spike gene, which is present in the consensus sequences of 67.4% of patients, is also highly diverse within hosts, with 29.7% of the public cohort being affected by this coexistence and exhibiting different variants. We also investigated the impact of several technical and epidemiological parameters on genetic heterogeneity and found that age, which is known to be correlated with poor disease outcomes, is a significant predictor of viral genetic diversity. Author SummarySince it arose in late 2019, the new coronavirus (SARS-CoV-2) behind the COVID-19 pandemic has mutated and evolved during its global spread. Individual patients may host different versions, or variants, of the virus, hallmarked by different mutations. We examine the diversity of genetic variants coexisting within patients across a cohort of 3939 publicly accessible samples and 749 recently sequenced samples from Switzerland. We find that a small number of patients carry most of the diversity, and that patients with more diversity tend to be older. We also find that most of the diversity is concentrated in certain regions and positions of the virus genome. In particular, we find that a variant reported to increase infectivity is among the most diverse positions. Our study provides a large-scale survey of within-patient diversity of the SARS-CoV-2 genome.

genomics↗

Phylogenomics of Mycobacterium africanum reveals a new lineage and a complex evolutionary history

Human tuberculosis is caused by members of the Mycobacterium tuberculosis Complex (MTBC). The MTBC comprises several human-adapted lineages known as M. tuberculosis sensu stricto as well as two lineages (L5 and L6) traditionally referred to as M. africanum. Strains of L5 and L6 are largely limited to West Africa for reasons unknown, and little is known on their genomic diversity, phylogeography and evolution. Here, we analyzed the genomes of 365 L5 and 326 L6 strains, plus five related genomes that had not been classified into any of the known MTBC lineages, isolated from patients from 21 African countries. Our population genomic and phylogeographical analyses show that the unclassified genomes belonged to a new group that we propose to name MTBC Lineage 9 (L9). While the most likely ancestral distribution of L9 was predicted to be East Africa, the most likely ancestral distribution for both L5 and L6 was the Eastern part of West Africa. Moreover, we found important differences between L5 and L6 strains with respect to their phylogeographical substructure, genetic diversity and association with drug resistance. In conclusion, our study sheds new light onto the genomic diversity and evolutionary history of M. africanum, and highlights the need to consider the particularities of each MTBC lineage for understanding the ecology and epidemiology of tuberculosis in Africa and globally.

genomics↗

Proteogenomic heterogeneity of localized human prostate cancer progression

BackgroundTumor-specific genomic aberrations are routinely determined by high throughput genomic measurements. It remains unclear though, how complex genome alterations affect molecular networks through changing protein levels, and consequently biochemical states of tumor tissues. ResultsHere, we investigated the propagation of genomic effects along the axis of gene expression during prostate cancer progression. For that, we quantified genomic, transcriptomic and proteomic alterations based on 105 prostate samples, consisting of benign prostatic hyperplasia regions and malignant tumors, from 39 prostate cancer patients. Our analysis revealed convergent effects of distinct copy number alterations impacting on common downstream proteins, which are important for establishing the tumor phenotype. We devised a network-based approach that integrates perturbations across different molecular layers, which identified a sub-network consisting of nine genes whose joint activity positively correlated with increasingly aggressive tumor phenotypes and was predictive of recurrence-free survival. Further, our data revealed a wide spectrum of intra-patient network effects, ranging from similar to very distinct alterations on different molecular layers. ConclusionsThis study uncovered molecular networks with remarkably convergent alterations across tumor sites and patients, but it also exposed a diversity of network effects: we could not identify a single sub-network that was perturbed in all high-grade tumor regions.

systems biology↗

Network analysis identifies regulators of lineage-specific phenotypes in Mycobacterium tuberculosis

The Mycobacterium tuberculosis (Mtb) complex includes ten phylogenetically distinct human-adapted lineages with varying geographical distributions and pathogenicity. Lineage 1 (L1) is associated with low virulence, while Lineage 2 (L2) is linked to hyper-virulence, increased transmission, and drug resistance. We performed multi-layer comparative analyses integrating whole-genome sequencing with quantitative transcriptomic and proteomic profiling of a panel of L1 and L2 clinical strains, each grown under two in vitro conditions. Our data revealed variable correlations between transcript and protein levels across strains and gene categories, indicating lineage-specific post-translational regulation. Transcriptional and translational differences scaled with phylogenetic distance, with one in three SNPs on average leading to gene expression changes. A newly developed genome-scale transcriptional regulatory model identified master transcription factors--closely linked to the sigma factor network--whose targets were differentially expressed between L1 and L2. Notably, DosR proteins showed higher basal levels and a stronger nitric oxide (NO) response in L2. Time-course validation using an Rv1985c induction and wild-type H37Rv under hypoxia and reaeration confirmed the role of Rv1985c in the differentially expressed genes between L1 and L2. These findings suggest that limited genetic variation can translate into significant phenotypic differences via differential regulation of key transcriptional networks. HighlightsO_LIProteomic and transcriptomic characterization of fully sequenced diverse L1 and L2 clinical strains of Mtb. C_LIO_LIPost translational control mechanisms for regulatory and virulence genes are mitigated in Mtb L2. C_LIO_LIA genome-scale transcriptional framework identifies DosR, Rv1985c, Lsr2 and Rv0691c as master transcription factors responsible for differential target gene expression in L2 compared to L1 strains. C_LIO_LIL1 and L2 DosR proteins respond differently to nitric oxide stress, thus determining a relevant phenotype. C_LIO_LITime-course phenotypic and transcriptomic data under hypoxia and reaeration validate Rv1985c as a key transcription factor differentiating L2 and L1 strains. C_LI

systems biology↗

Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping

Predicting quantitative effects of gene regulatory elements (GREs) on gene expression is a longstanding challenge in biology. Machine learning models for gene expression prediction may be able to address this challenge, but they require experimental datasets that link large numbers of GREs to their quantitative effect. However, current methods to generate such datasets experimentally are either restricted to specific applications or limited by their technical complexity and error-proneness. Here we introduce DNA-based phenotypic recording as a widely applicable and practical approach to generate very large datasets linking GREs to quantitative functional readouts of high precision, temporal resolution, and dynamic range, solely relying on sequencing. This is enabled by a novel DNA architecture comprising a site-specific recombinase, a GRE that controls recombinase expression, and a DNA substrate modifiable by the recombinase. Both GRE sequence and substrate state can be determined in a single sequencing read, and the frequency of modified substrates amongst constructs harbouring the same GRE is a quantitative, internally normalized readout of this GREs effect on recombinase expression. Using next-generation sequencing, the quantitative expression effect of extremely large GRE sets can be assessed in parallel. As a proof of principle, we apply this approach to record translation kinetics of more than 300,000 bacterial ribosome binding sites (RBSs), collecting over 2.7 million sequence-function pairs in a single experiment. Further, we generalize from these large-scale datasets by a novel deep learning approach that combines ensembling and uncertainty modelling to predict the function of untested RBSs with high accuracy, substantially outperforming state-of-the-art methods. The combination of DNA-based phenotypic recording and deep learning represents a major advance in our ability to predict quantitative function from genetic sequence.

synthetic biology↗

Establishing Probiotic Saccharomyces boulardii as a Model Organism for Synthesis and Delivery of Biomolecules

Saccharomyces boulardii is a widely used yeast probiotic which can counteract various gastrointestinal disorders1. As a relative of Saccharomyces cerevisiae, S. boulardii exhibits rapid growth and is easy to transform2 and thus represents a promising chassis for the engineered secretion of biomolecules. To establish S. boulardii as a platform for delivery of biomolecules to the mammalian gut, we measured the amount and variance in protein expression enabled by promoters, terminators, selective markers, and copy number control elements in this organism. These genetic elements were characterized in plasmidic and genomic contexts, revealing strategies for tunable control of gene expression and CRISPR-mediated genome editing in this strain. We then leveraged this set of genetic parts to combinatorially assemble pathways enabling a wide range of drug and vitamin titers. Finally, we measured S. boulardiis residence time in the gastrointestinal tracts of germ-free and antibiotic-treated mice, revealing the relationships between dosing strategy and colonization level. This work establishes S. boulardii as a genetically tractable commensal fungus and provides a set of strategies for engineering S. boulardii to synthesize and deliver biomolecules during gut colonization.

synthetic biology↗

Resource misallocation as a mediator of fitness costs in antibiotic resistance.

Antimicrobial resistance poses a threat to global health and the economy. It is widely accepted that, in the absence of antibiotics, drug resistance mutations carry a fitness cost. In the case of rifampicin resistance in fast-growing bacteria, this cost stems from a reduced transcription rate of the RNA polymerase resulting in slower ribosome biosynthesis. However, this relationship does not apply in the slow-growing Mycobacterium tuberculosis, where the true mechanism of fitness cost of rifampicin resistance as well as the impact of compensatory evolution remain unknown. Here we show, using global transcriptomic and proteomic profiling of selected M. tuberculosis mutants and clinical strains, that the fitness cost of rifampicin resistance in M. tuberculosis is the result of the physiological burden caused by aberrant gene expression. We further show that the perceived burden can be increased, effectively suppressing the emergence of drug resistance.

microbiology↗

Multiple Introductions of the Mycobacterium tuberculosis Lineage 2 Beijing into Africa over centuries

The Lineage 2-Beijing (L2-Beijing) sub-lineage of Mycobacterium tuberculosis has received much attention due to its high virulence, fast disease progression, and association with antibiotic resistance. Despite several reports of the recent emergence of L2-Beijing in Africa, no study has investigated the evolutionary history of this sub-lineage on the continent. In this study, we used whole genome sequences of 817 L2 clinical strains from 14 geographical regions globally distributed to investigate the origins and onward spread of this lineage in Africa. Our results reveal multiple introductions of L2-Beijing into Africa linked to independent bacterial populations from East-and Southeast Asia. Bayesian analyses further indicate that these introductions occurred during the past 300 years, with most of these events pre-dating the antibiotic era. Hence, the success of L2-Beijing in Africa is most likely due to its hypervirulence and high transmissibility rather than drug resistance.

evolutionary biology↗

Reference Set of Mycobacterium tuberculosis Clinical Strains: A tool for research and product development

The Mycobacterium tuberculosis complex (MTBC) causes tuberculosis (TB) in humans and various other mammals. The human-adapted members of the MTBC comprise seven phylogenetic lineages that differ in their geographical distribution. There is growing evidence that this phylogenetic diversity modulates the outcome of TB infection and disease. For decades, TB research and development has focused on the two canonical MTBC reference strains H37Rv and Erdman, both of which belong to Lineage 4. Relying on only a few laboratory-adapted strains can be misleading as study results might not be directly transferrable to clinical settings where patients are infected with a diverse array of strains, including drug-resistant variants. Here, we argue for the need to expand TB research and development by incorporating the phylogenetic diversity of the MTBC. To facilitate such work, we have assembled a group of 20 genetically well-characterized clinical strains representing the seven known human-adapted MTBC lineages. With the \"MTBC clinical strains reference set\" we aim to provide a standardized resource for the TB community. We hope it will enable more direct comparisons between studies that explore the physiology of MTBC beyond the lab strains used thus far. We anticipate that detailed phenotypic analyses of this reference strain set will increase our understanding of TB biology and assist in the development of new control tools that are universally effective.

microbiology↗

A New Phylogenetic Framework for the Animal-adapted Mycobacterium tuberculosis Complex

Tuberculosis (TB) affects humans and other animals and is caused by bacteria from the Mycobacterium tuberculosis complex (MTBC). Previous studies have shown that there are at least nine members of the MTBC infecting animals other than humans; these have also been referred to as ecotypes. However, the ecology and the evolution of these animal-adapted MTBC ecotypes are poorly understood. Here we screened 12,886 publicly available MTBC genomes and newly sequenced 17 animal-adapted MTBC strains, gathering a total of 529 genomes of animal-adapted MTBC strains. Phylogenomic and comparative analyses confirm that the animal-adapted MTBC members are paraphyletic with some members more closely related to the human-adapted Mycobacterium africanum Lineage 6 than to other animal-adapted strains. Furthermore, we identified four main animal-adapted MTBC clades that might correspond to four main host shifts; two of these clades are proposed to reflect independent cattle domestication events. Contrary to what would be expected from an obligate pathogen, MTBC nucleotide diversity was not positively correlated with host phylogenetic distances, suggesting that host tropism in the animal-adapted MTBC seems to be driven more by contact rates and demographic aspects of the host population rather than host relatedness. By combining phylogenomics with ecological data, we propose an evolutionary scenario in which the ancestor of Lineage 6 and all animal-adapted MTBC ecotypes was a generalist pathogen that subsequently adapted to different host species. This study provides a new phylogenetic framework to better understand the evolution of the different ecotypes of the MTBC and guide future work aimed at elucidating the molecular mechanisms underlying host specificity.

evolutionary biology↗