Biology subjects

Popinga, A.

Publications and source records attributed to Popinga, A..

4 recordsLinked to original sources

bioRxiv2026

Integrating Single-Cell Experiments and Stochastic Models to Understand and Predict Glucocorticoid Receptor Transport and DUSP1 mRNA Expression Dynamics

Glucocorticoids activate the glucocorticoid receptor (GR) to suppress inflammation, yet it remains unclear how GR transport dynamics and downstream gene regulation are coordinated within single cells. We combine immunocytochemistry (ICC) and single-molecule fluorescence in situ hybridization (smFISH) to quantify endogenous GR transport and DUSP1 transcription dynamics across thousands of individual cells following dexamethasone (Dex) stimulation. Performing multiple rounds of statistical inference based on Chemical Master Equations (CME), we determine the most likely mechanisms and reaction rates for Dex-driven GR nuclear import; compartment-specific GR degradation; GR-dependent control of the DUSP1 promoter; and DUSP1 transcription, elongation, transport, and degradation. Our inferred model suggests that nuclear GR degradation is the dominant mechanism of receptor clearance, that GR primarily regulates promoter activation, and that time-dependent AU-rich element (ARE)-mediated mRNA degradation contributes heavily to DUSP1 clearance. With these mechanisms, the fully-parameterized model quantitatively predicts joint distributions of GR translocation and decay dynamics, DUSP1 transcription site activity, and nuclear and cytoplasmic DUSP1 mRNA heterogeneity among clonal cells as functions of time and across seven orders of magnitude for Dex induction concentrations. Our results establish an integrated quantitative framework to link receptor dynamics to gene expression heterogeneity and predict single-cell hormone-responsive transcription programs.

cell biology↗

bioRxiv2020

Class I Aminoacyl-tRNA Synthetase Urzyme and CP1 Modules have Distinct Genetic Origins

The provenance of the aminoacyl-tRNA synthetases (aaRS) poses unusually challenging questions because of their role in the emergence and evolution of genetic coding. We investigate evidence about their ancestry from highly curated structure-based multiple sequence alignments of a small "scaffold" that is structurally invariant in all 10 canonical Class I aaRS. Statistically different values of two uncorrelated phylogenetic metrics--residue by residue conservation derived from Clustal and row-by-row cladistic congruence derived from BEAST2--suggest that the Class I scaffold is a mosaic assembled from distinct, successive genetic sources. These data are especially significant in light of: (i) experimental fragmentations of the Class I scaffold into three partitions that retain catalytic activities in proportion to their length; and (ii) multiple sources of evidence that two of these partitions arose from an ancestral Class I aaRS gene encoding a Class II ancestor in frame on the opposite strand. Two additional metrics output by BEAST2 vary in accordance with the presumed functionality endowed by the various modules. The new evidence supplements previous aaRS phylogenies. It identifies a previously characterized 46-residue Class I "protozyme" as preceding the adaptive radiation of the superfamily containing variations of the Rossmann dinucleotide binding fold related to amino acid discrimination, and thus as root of that molecular tree. Such a rooting is consistent with near simultaneous emergence of genetic coding and the origin of the proteome, resolving a conundrum posed by previous inferences that Class I aaRS evolved long after the genetic code had been implemented in an RNA world. Further, it establishes a timeline for the growth of coding from a binary amino acid alphabet by pinpointing discontinuous enhancements of aaRS fidelity. Author SummaryPhylogenetic analysis uncovers evolutionary connections between different protein superfamily members. We describe complementary, uncorrelated, phylogenetic metrics that support multiple evolutionary histories for different segments within members of the Class I aminoacyl-tRNA synthetase superfamily. Using a carefully curated 3D crystal structure superposition as the primary source of the multiple sequence alignment substantially reduced dependence of these metrics on empirical amino acid substitution matrices. Two metrics are derived from the amino acid distribution observed in each successive position. A third depends on how individual sequences distribute into phylogenetic tree branches for each of the ten amino acids activated by the superfamily. All metrics confirm that a segment previously identified as an inserted element is, indeed, a more recent acquisition, despite its structural conservation. The residue-by-residue conservation metrics reveal significant co-variation of mutational frequencies between a core segment that forms the amino acid binding site and a neighboring segment derived from the more recent insertion element. We attribute that covariation to the differentiation of superfamily members as evolutionary divergence enhanced amino acid specificity. Finally, evidence that the insertion element is a recent acquisition implies a new branching order for much of the proteome.

evolutionary biology↗

bioRxiv2019

Mitogenomic Diversity in Sacred Ibis Mummies sheds light on early Egyptian practices

The ancient catacombs of Egypt harbor millions of well-preserved mummified Sacred Ibis (Threskiornis aethiopicus) dating from [~]600BC. Although it is known that a very large number of these votive mummies were sacrificed to the Egyptian God Thoth, how the ancient Egyptians obtained millions of these birds for mummification remains unresolved. Ancient Egyptian textual evidences suggest they may have been raised in dedicated large-scale farms. To investigate the most likely method used by the priests to secure birds for mummification, we report the first study of complete mitochondrial genomes of 14 Sacred Ibis mummies interred [~]2500 years ago. We analysed and compared the mitogenomic diversity among Sacred Ibis mummies to that found in modern Sacred Ibis populations from throughout Africa. The ancient birds show a high level of genetic variation comparable to that identified in modern African populations, contrary to the suggestion in ancient hieroglyphics (or ancient writings) of centralized industrial scale farming of sacrificial birds. This suggests a sustained short-term taming of the wild Sacred Ibis for the ritual yearly demand.

evolutionary biology↗

bioRxiv2018

BEAST 2.5: An Advanced Software Platform for Bayesian Evolutionary Analysis

Elaboration of Bayesian phylogenetic inference methods has continued at pace in recent years with major new advances in nearly all aspects of the joint modelling of evolutionary data. It is increasingly appreciated that some evolutionary questions can only be adequately answered by combining evidence from multiple independent sources of data, including genome sequences, sampling dates, phenotypic data, radiocarbon dates, fossil occurrences, and biogeographic range information among others. Including all relevant data into a single joint model is very challenging both conceptually and computationally. Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have played a key role in these developments.\n\nDeveloping such software frameworks is increasingly a major scientific activity in its own right, and comes with specific challenges, from practical software design, development and engineering challenges to statistical and conceptual modelling challenges. BEAST 2 is one such computational software platform, and was first announced over 4 years ago. Here we describe a series of major new developments in the BEAST 2 core platform and model hierarchy that have occurred since the first release of the software, culminating in the recent 2.5 release.\n\nAuthor summaryBayesian phylogenetic inference methods have undergone considerable development in recent years, and joint modelling of rich evolutionary data, including genomes, phenotypes and fossil occurrences is increasingly common. Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have played a key role in these developments. Developing scientific software is increasingly crucial to advancement in many fields of biology. The challenges range from practical software development and engineering, distributed team coordination, conceptual development and statistical modelling, to validation and testing. BEAST 2 is one such computational software platform for phylogenetics, population genetics and phylodynamics, and was first announced over 4 years ago. Here we describe the full range of new tools and models available on the BEAST 2.5 platform, which expand joint evolutionary inference in many new directions, especially for joint inference over multiple data types, non-tree models and complex phylodynamics.

evolutionary biology↗