Biology subjects

Aguirre, J. D.

Publications and source records attributed to Aguirre, J. D..

4 recordsLinked to original sources

bioRxiv2025

Mapping the latent CRBN-molecular glue degrader interactome

Molecular glue degraders (MGDs) are a transformative modality in drug discovery. MGDs that work in concert with the E3 ligase CRL4CRBN can degrade a range of substrates through tailored MGDs. To explore CRL4CRBN reprogrammability, we tested whether reported CRBN-MGD substrates are part of a network of latent CRBN interactors, detectable with generic CRBN-MGDs. Leveraging highly parallel interaction measurement (GluePCA) between CRL4CRBN and human zinc-fingers (ZFs), we identified [~]210 ZFs bound to CRBN-pomalidomide, where top binders are already reported as degraded by dedicated MGDs. To map latent CRBN-MGDs interactions proteome-wide, and thus define the immediately accessible CRBN target space, we combined AI-derived protein surface queries (MaSIF-mimicry) with GluePCA. This pipeline identified 6 known and 43 novel CRBN-pomalidomide binders, thereby providing privileged starting points for MGD development. We expect this binding-focused, highly parallel workflow to be readily applicable to other MGD/E3 ligase systems, extending the target landscape of this emerging drug class.

molecular biology↗

bioRxiv2025

Synaptic MEMOIR: mapping individual synapses of neurons with protein barcodes

Obtaining wiring diagrams of brains has been a major achievement for neuroscience. However, an underlying challenge in connectomics is the fundamental tradeoff between the imaging resolution needed to resolve synapses and the volume of the brain that can be imaged. For example, electron microscopy (EM) visualizes synaptic sites with ~5 nm resolution, but is difficult to scale beyond volumes of 1 mm3. Here, we present Synaptic MEMOIR (Memory with Engineered Mutagenesis with Optical in situ Readout) that enables imaging of neuronal projections in animal brains with single-synapse resolution. Synaptic MEMOIR is built around three key design features. First, protein barcodes are transported to synapses to allow matching of synaptic barcodes to cell body barcodes without high resolution imaging and the error-prone process of tracing neuronal processes across long distances. Second, Synaptic MEMOIR uses continuous mutagenesis to generate a large diversity of barcodes to uniquely label cell bodies and synapses. Last, the timing of recombination and transport can be tuned to record synaptic age or projection information. Combining these features, we demonstrated projection mapping of 113 neurons in the Drosophila melanogaster optic lobe in a volume of 9.5 million m3. Because synapses are identified by transported barcodes with optical microscopy at 300 nm resolution, this approach can potentially scale to much larger volumes, similar at least to those imaged in recent mouse brain transcriptomics atlases. In addition, synaptic MEMOIR can match barcodes across brain sections, and does not require tissue clearing to track long-range projections. Together, these results provide the foundation for a scalable optical image-based system for reconstructing the neural wiring diagrams of brains across different developmental stages, genetic backgrounds and perturbations. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=46 SRC="FIGDIR/small/690442v1_ufig1.gif" ALT="Figure 1"> View larger version (14K): org.highwire.dtl.DTLVardef@8363cdorg.highwire.dtl.DTLVardef@d3240org.highwire.dtl.DTLVardef@5e2793org.highwire.dtl.DTLVardef@1784f2a_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2024

A novel framework for assessing the robustness of genomic animal models applied to a wild marine fish

In highly dispersive taxa, gene flow can homogenise genetic variation over broad spatial and temporal scales. However, phenotypic differentiation can still arise when heritable genetic variation is available to selection and (or) when organisms exhibit plasticity. Disentangling heritable versus non-heritable components of variation is possible using genomic animal models, but this approach has been underused in wild organisms. We investigated head shape variation in the marine cryptobenthic fish Bathygobius cocosensis, a highly dispersive species occupying heterogeneous environments. Head shape, a diet-related trait, is spatially structured in Australian populations. We curated a unique dataset comprising genotypic, phenotypic, and environmental variation to: (1) contrast the scales over which genetic and phenotypic variation are structured; and (2) quantify heritable versus non-heritable contributions to head shape variation using genomic animal models and comparisons between FST, PST, and QST. At macrogeographic scales (hundreds of kilometres) and over time (2 years), phenotypic differentiation (0.0001 [≤] PST [≤] 0.47) exceeded both genomic and additive genetic differentiation (0.001 [≤] FST[≤] 0.004 and 0.00001 [≤] QST [≤] 0.004, respectively). This suggests head shape variation may primarily reflect (non-heritable) plastic responses, rather than (heritable) adaptive genetic changes in mean head shape. At microgeographic scales, associations between head shape and tide pool variables were temporally variable, indicating that local environmental conditions may structure phenotypes within populations. Overall, this study highlights the value of genomic animal models for disentangling heritable and non-heritable components of phenotypic variation in dispersive marine taxa. It provides an integrative analysis linking genetic, phenotypic, and environmental variation in a cryptobenthic fish, highlighting how phenotypic divergence can emerge without strong genetic differentiation, and challenging the common assumption that phenotypic divergence necessarily implies adaptation.

genomics↗

bioRxiv2019

Connecting micro and macroevolution using genetic incompatibilities and natural selection on additive genetic variance

Testing whether local adaptation and intrinsic reproductive isolation share a genetic basis can reveal important connections between adaptation and speciation. Local adaptation arises as advantageous alleles spread through a population, but whether these same advantageous alleles fail on the genetic backgrounds of other populations remains largely unknown. We used a quantitative genetic breeding design to produce a late generation (F4) recombinant hybrid population by equally mating amongst four contrasting ecotypes of a native Australian daisy for four generations. We tracked fitness across generations and measured morphological traits in the glasshouse, and used a reciprocal transplant to quantify fitness in all four parental habitats. In the glasshouse, plants in the second generation showed a reduction in fitness as a loss of fertility, but this was fully recovered in the following generation. The F4 hybrid lacked extreme phenotypes present in the parental ecotypes, suggesting that genes reducing hybrid fitness were linked to traits specific to each ecotype. In the natural habitats, additive genetic variance for fitness was greatest for habitats that showed stronger native-ecotype advantage, suggesting that a loss of genetic variation present in the parental ecotypes were adaptive in the natural habitats. Reductions in genetic variance for fitness were associated with a loss of ecological trade-offs previously described in the parental ecotypes. Furthermore, natural selection on morphological traits differed amongst the parental habitats, but was not predicted to occur towards the morphology of the parental ecotypes. Together, these results suggest that intrinsic reproductive isolation removed adaptive genetic variation present in the parental ecotypes. The evolution of these distinct ecotypes was likely governed by genetic variation that resulted in both ecological trade-offs and intrinsic reproductive isolation among populations adapted to contrasting environments.

evolutionary biology↗