Biology subjects

Aldrich, R. W.

Publications and source records attributed to Aldrich, R. W..

4 recordsLinked to original sources

bioRxiv2025

Database Permeating through Time, Space, and Medicine: A sequence, structure, and clinical compilation and comparison of transmembrane amino acids in VGL ion channels

Ion channels of the VGL superfamily are extremely diverse in their physiological roles - critical in all excitable cells. Mutations in these channels can cause clinical deficits and symptomologies. With recent advances in sequencing and structural data in the past 30 years, there is a plethora of bioinformatic information that experimentalists can utilize to draw hypotheses about structure and function. However, there is no cohesive database that has compiled this data and presents it in an easily accessible and avoids the confounds of close evolutionary lineages. Here, we seek to fill this gap in resources by compiling and comparing groups of sequences and structures across many channels of the VGL superfamily. Additionally, we corroborate the well-conserved amino acid positions with previous experimental work as well as put forth some understudied but well-conserved amino acid positions that might be fundamental to the certain generalizable mechanisms present in the VGL superfamily channels. To further lend evidence to understudied positions being critical to certain generalizable mechanisms, we also compiled clinical mutation data at these positions across many channels to show the likely functional relevance of these positions. Finally, we will make all of the alignments and resources we generated publicly available at https://github.com/Frank-Yeh-95/VGLDatabaseCompilation for ease of hypothesis generation.

biophysics↗

bioRxiv2022

Calcium dependence of both lobes of calmodulin is involved in SK channel gating

KCa2.1-3 Ca2+-activated K+-channels (SK) require calmodulin to gate in response to cellular Ca2+. A model for SK gating proposes that the N-terminal domain (N-lobe) of calmodulin is required for activation, but an immobile C-terminal domain (C-lobe) has constitutive, Ca2+-independent binding. Although structures support a domain-driven hypothesis of SK gate activation by calmodulin, only a partial understanding is possible without measuring both channel activity and protein binding. We measured SK2 (KCa2.2) activity using inside-out patch recordings. Currents from calmodulin-disrupted SK2 channels can be restored with exogenously applied calmodulin. We find that SK2 activity only approaches full activation with full-length calmodulin with both an N- and C-lobe. We measured calmodulin binding to a C-terminal SK peptide (SKp) using both composition-gradient multi-angle light scattering and tryptophan emission spectra. Isolated lobes bind to SKp with high affinity, but isolated lobes do not rescue SK2 activity. Consistent with earlier models, N-lobe binding to SKp is stronger in Ca2+, and C-lobe binding affinity is strong independent of Ca2+. However, a native tryptophan in SKp is sensitive to Ca2+ binding to both the N- and C-lobes of calmodulin at Ca2+ concentrations that activate SK2, demonstrating that the C-lobe interaction with SKp changes with Ca2+. Our peptide binding data and electrophysiology show that SK gating models need deeper scrutiny. We suggest that the Ca2+-dependent associations of both lobes of calmodulin to SKp are crucial events during gating. Additional investigations are necessary to complete a mechanistic gating model consistent with binding, physiology, and structure.

biophysics↗

bioRxiv2020

Mapping Functional Protein Neighborhoods in the Mouse Brain

New proteomics methods make it possible to determine protein interaction maps at the proteome scale without the need for genetically encoded tags, opening up new organisms and tissue types to investigation. Current molecular and computational methods are oriented towards protein complexes that are soluble, stable, and discrete. However, the mammalian brain, among the most complicated and most heavily studied tissue types, derives many of its unique functions from protein interactions that are neither discrete nor soluble. Proteomics investigations into the global protein interaction landscape of the brain have therefore leveraged non-proteomics datasets to supplement their experiments. Here, we develop a novel, integrative proteomics pipeline and apply it to infer a global map of functional protein neighborhoods in the mouse brain without the aid of external datasets. By leveraging synaptosome enrichment and interactomics methods that target both soluble and insoluble protein fractions, we resolved protein interactions for key neural pathways, including those from refractory subcellular fractions such as the membrane and cytoskeleton. In comparison to external datasets, our observed interactions perform similarly to hand-curated synaptic protein interactions while also suggesting thousands of novel connections. We additionally employed cleavable chemical cross-linkers to detect direct binding partners and provide structural context. Our combined map suggests new protein pathways and novel mechanisms for proteins that underlie neurological diseases, including autism and epilepsy. Our results show that proteomics methods alone are sufficient to determine global interaction maps for proteins that are of broad interest to neuroscience. We anticipate that our map will be used to prioritize new research avenues and will pave the way towards future proteomics techniques that resolve protein interactions at ever greater resolution.

systems biology↗

bioRxiv2018

Ancestral Reconstruction of Protein Interaction Networks

The molecular and cellular basis of novelty is a major open question in evolutionary biology. Until very recently, the vast majority of cellular phenomena were so difficult to sample that cross-species studies of biochemistry were rare and comparative analysis at the level of biochemical systems was almost impossible. Recent advances in systems biology are changing what is possible, however, and comparative phylogenetic methods that can handle this new data are wanted. Here, we introduce the term \"phylogenetic latent variable models\" (PLVMs, pronounced \"plums\") for a class of models that has recently been used to infer the evolution of cellular states from systems-level molecular data, and develop a new parameterization and fitting strategy that is useful for comparative inference of biochemical networks. We deploy this new framework to infer the ancestral states and evolutionary dynamics of protein-interaction networks by analyzing >16,000 predominantly metazoan co-fractionation and affinity-purification mass spectrometry experiments. Based on these data, we estimate ancestral interactions across unikonts, broadly recovering protein complexes involved in translation, transcription, proteostasis, transport, and membrane trafficking. Using these results, we predict an ancient core of the Commander complex made up of CCDC22, CCDC93, C16orf62, and DSCR3, with more recent additions of COMMD-containing proteins in tetrapods. We also use simulations to develop model fitting strategies and discuss future model developments.

evolutionary biology↗