Biology subjects

Heron, M.

Publications and source records attributed to Heron, M..

4 recordsLinked to original sources

bioRxiv2026

LAMA2-related muscular dystrophy alters Schwann cell calcium homeostasis and increases peripheral nerve inflammation

LAMA2-related muscular dystrophy (LAMA2-RD) affects skeletal muscle and peripheral nerves, yet the consequences of LAMA2 deficiency on peripheral nerve integrity beyond early postnatal development remain incompletely understood. We investigated sciatic nerve architecture and molecular alterations across postnatal life in hypomorphic Lama2dy2J/dy2J mice. LAMA2 localizes around the abaxonal surface of myelinating Schwann cells in control nerves. LAMA2-deficient nerves exhibited patchy regions lacking myelinated axons from early postnatal stages into adulthood, including expanded Remak bundles along with axons completely lacking normal Schwann cell ensheathment. In adult nerves, myelin infolding and reduced myelin circularity revealed abnormalities in the architecture of myelin that had formed. Bulk sciatic nerve RNA sequencing identified altered calcium-signaling and immune-related transcriptional signatures. Complementary Fura Red measurements in primary nerve-derived Schwann cell cultures demonstrated decreased intracellular calcium in LAMA2-deficient samples, while ATP-evoked responses were preserved. Older LAMA2-deficient nerves also exhibited increased CD45+CD11b+ myeloid-cell infiltration. Together, these observations extend the characterization of LAMA2-associated neuropathy into adulthood and identify calcium homeostasis and neuroimmune responses as candidate processes relevant to persistent peripheral nerve pathology.

neuroscience↗

bioRxiv2025

The fitness costs of reproductive specialization scale inversely with organismal size

The evolution of reproductive specialization represents a fundamental innovation in multicellular life, yet the conditions favoring its evolution remain poorly understood. Here, we develop a population genetic framework that examines the fitness cost of reproductive specialization as a function of organism size. We show analytically that the costs of specialization decrease dramatically with organism size. For example, while a 4-cell organism with 50% somatic cells experiences a 50% reduction in population-level exponential growth rate (the same as the two-fold cost of sex), a hundred-cell organism faces only a 15% reduction, a thousand-cell organism 10%, a million-cell organism 5%, and a billion-cell organism merely 3.3%. This scaling relationship arises from the fact that proportionally more cellular growth in larger organisms is required for development, reducing the rate at which the fitness costs of specialization are compounded over multicellular generations. We contextualize our mathematical model with data from the volvocine green algae, showing that simple theoretical predictions closely match empirical measurements. While cellular differentiation demands that somatic advantages compensate for lost reproductive potential, we demonstrate that these compensatory requirements diminish with the logarithm of organism size, fundamentally altering the cost-benefit landscape for large organisms and potentially driving the evolution of a size-differentiation ratchet. This size-scaling relationship helps explain the broad association between large organismal size and multicellular complexity.

evolutionary biology↗

bioRxiv2020

Large-scale analysis of Drosophila core promoter function using synthetic promoters

The core promoter, the region immediately surrounding the transcription start site, plays a central role in setting metazoan gene expression levels, but how exactly it computes expression remains poorly understood. To dissect core promoter function, we carried out a comprehensive structure-function analysis to measure synthetic promoters activities, with and without an external stimulus (hormonal activation). By using robotics and a dual-luciferase reporter assay, we tested [~]3000 mutational variants representing 19 different Drosophila melanogaster promoter architectures. We explored the impact of different types of mutations, including knockout of individual sequence motifs and motif combinations, variations of motif strength, positioning, and flanking sequences. We observe strong effects of the mutations on activity, and a linear combination of the individual motif features can largely account for the combinatorial effects on core promoter activity. Our findings shed new light on the quantitative assessment of gene expression, a fundamental process in all metazoans.

systems biology↗

bioRxiv2020

Deconvolving nuclesome binding energy from experimental errors

1Eukaryotic genomes are compacted into nucleosomes, 147-bp of DNA wrapped around histone proteins. Nucleosomes can hinder transcription factors and other DNA-binding proteins from accessing the genome. This competition at promoters and enhancers regulates gene expression. Therefore, a quantitative understanding of gene regulation requires the quantitative prediction of nucleosome binding affinities. However, little is known for certain about the sequence preference of nucleosomes. Here we develop an integrated model of nucleosome binding and genome-wide measurements thereof. Our model learns similar nucleosome sequence preferences from MNase-Seq and CC-Seq datasets. We find that modelling the positional uncertainty of MNase-Seq deconvolves the commonly described smooth 10-bp-periodic sequence preference into a position-specific pattern more closely resembling the pattern obtained from high-resolution CC-Seq data. By analysing the CC-Seq data we reveal the strong preference of A/T at +/- 3 bp from the dyad as an experimental bias. Our integrated model can separate this bias of CC-Seq from the true nucleosome binding preference. Our results show that nucleosomes have position-specific sequence preferences, which probably play an important role in their competition with transcription factors. Furthermore, our comparison of diverse datasets shows that the experimental biases have a similar strength as the signal of nucleosome-positioning measurements. Validating nucleosome models on experiments with similar biases overestimates their prediction quality of the true nucleosome binding. There are still many open questions about the sequence preference of nucleosomes and our approach will need to be extended to answer them. Only integrated models that combine the thermodynamics of nucleosome binding with experimental errors can deconvolve the two and learn the true preferences of nucleosomes.

molecular biology↗