Biology subjects

Mathis, M.

Publications and source records attributed to Mathis, M..

4 recordsLinked to original sources

bioRxiv2026

Genetic Code Expansion for Site-Specific Encoding of a Switchable, Intrinsic Fluorophore-Quencher Pair to Monitor Protein Dynamics

Precisely modifying proteins at multiple sites in their native, folded structures offers unique opportunities to answer molecular and cellular-level biological questions. Here, we present a genetic code expansion strategy for site-specific integration of a fluorophore-quencher pair comprising two non-canonical amino acids--acridonylalanine (Acd) and methyltetrazinyl phenylalanine (Tet) -- into a protein expressed in E. coli. The Acd and Tet pair requires no post-translational labeling, and quenching can be switched off by biorthogonal or photochemical reactions of Tet for convenient internal control experiments. Mechanistic studies based on Stern-Volmer quenching, fluorescence lifetime measurements, and "proline ruler" peptides established the distance dependence of quenching. As proof-of-concept, we applied this strategy to study: 1) calmodulin, a calcium-sensing protein, 2) RecA, a DNA damage sensor in bacteria, and 3) LexA, a transcriptional repressor whose activation by RecA governs acquired antibiotic resistance in bacteria. Using these proteins, we demonstrate that dual Acd/Tet labeling provides molecular-level insights into protein dynamics, enables high-throughput drug screening, and advances tools for studying protein structure-function relationships.

biochemistry↗

bioRxiv2024

An operational framework to map Essential Life Support Areas (ELSAs) for biodiversity, climate, and sustainable development

Almost all countries are making increasingly bold commitments to halt and reverse biodiversity loss, minimise the impacts of climate change, and transition to more sustainable development. The effective achievement of many of these commitments relies on integrated spatial planning frameworks that are adaptable to national circumstances, priorities and capabilities. This need is formally recognized by Target 1 of the Kunming-Montreal Global Biodiversity Framework (GBF), which specifies that all areas should be under such planning. Here, we describe the development and application of an operational framework for national-level integrated spatial planning: Essential Life Support Areas (ELSAs). This framework facilitates the identification of areas that - if protected, restored, or sustainably managed - can support the achievement of national commitments to biodiversity, climate, and sustainable development. The process of mapping ELSAs relies heavily on leadership by national experts and stakeholders and the integration of spatial data using systematic conservation planning tools. We showcase the ELSA process carried out for Ecuador, where the use of real-time scenario analyses enabled diverse stakeholder groups to collaborate to assess national priorities for nature, climate, and sustainable development, view trade-offs and synergies, and arrive at a spatial plan to guide national action. ELSA presented an actionable approach for Ecuador, and 12 other pilot countries, to create a spatial plan aimed at fulfilling their national and international commitments to nature, including to the GBF.

ecology↗

bioRxiv2024

Neuro-musculoskeletal modeling reveals muscle-level neural dynamics of adaptive learning in sensorimotor cortex

The neural activity of the brain is intimately coupled to the dynamics of the body. In order to predict and adapt to the sensorimotor consequences of our actions, compelling behavioral studies in humans, non-human primates, and in rodents have shown the existence of internal models - predictive models of our body in the environment. These internal models are theoretically used to compute an updated state estimate with prediction errors. Here, we directly test whether such errors are encoded in primary somatosensory (S1) or motor (M1) cortex during a motor adaptation task in mice. Using control theory-derived features that include prediction errors, we find that functionally distinct neurons are mapped onto specific computational motifs. We find that layer 2/3 population dynamics encode command-like signals and sensorimotor prediction errors (SPEs). S1 neurons encode SPEs more prominently than M1, and the neural latent dynamics change in S1 more than in M1 during this within-session learning. Then we asked, in which coordinate frameworks are such errors computed? To do this, we developed a novel 50-muscle model of the adult mouse forelimb that is capable of studying motor control and learning in a physics simulator. We identify both high-level 3D position and muscle spaces as coordinate frameworks for SPEs. Together, our results provide a new model of how neural dynamics in S1 enables adaptive learning.

neuroscience↗

bioRxiv2017

Genome-wide analysis yields new loci associating with aortic valve stenosis

Aortic valve stenosis (AS) is the most common valvular heart disease, characterized by a thickened and calcified valve causing left ventricular outflow obstruction. Severe AS is a significant cause of morbidity and mortality, affecting approximately 5% of those over 70 years of age1,2,3. Little is known about the genetics of AS, although recently a variant at the LPA locus4 and a rare MYH6 missense variant were found to associate with AS5. We report a large genome-wide association study (GWAS) with a follow-up in up to 7,307 AS cases and 801,073 controls. We identified two new AS loci, on chromosome 1p21 near PALMD (rs7543130; OR=1.20, P=1.2x10-22) and on chromosome 2q22 in TEX41 (rs1830321; OR=1.15, P=1.8x10-13). Rs7543130 also associates with bicuspid aortic valve (BAV) (OR=1.28, P=6.6x10-10) and aortic root diameter (P=1.30x10-8) and rs1830321 associates with BAV (OR=1.12, P=5.3x10-3 and coronary artery disease (CAD) (OR=1.05, P=9.3x10-5). These results indicate that AS is partly rooted in the same processes as cardiac development and atherosclerosis.

genetics↗