Biology subjects

Sondek, J.

Publications and source records attributed to Sondek, J..

9 recordsLinked to original sources

bioRxiv2026

PHENOMS: Open-Source Software for Rust-Accelerated Hydrogen-Bond Analysis in Molecular Dynamics Simulations

Hydrogen-deuterium exchange mass spectrometry (HDX-MS) provides powerful insight into protein structure and dynamics, but interpretation of protection patterns at atomic resolution often requires complementary computational modeling. We present PHENOMS, an open-source Python package that integrates molecular dynamics trajectories with HDX-MS data to analyze backbone hydrogen-bond networks by tracking how individual hydrogen bonds and residue-residue contacts form, break, and reorganize throughout the simulations. This residue-level analysis can reveal local structural changes that may be missed by conventional global trajectory metrics. PHENOMS employs a multithreaded, Rust-accelerated computational engine that achieved an average 16-fold speedup (up to 100-fold) over widely used Python-based MD analysis packages in our benchmarks, while retaining individual hydrogen-bond resolution in every trajectory frame. We demonstrate PHENOMS through multiple retrospective case studies using published and in-house datasets, showing that it can recapitulate HDX-MS protection patterns, identify key residues that drive coordinated structural changes, and benchmark the computational efficiency of the approach. With automated quality-control workflows, PHENOMS provides a framework for integrating hydrogen-bond analysis with HDX-MS data or serves as a standalone, high-throughput tool for analyzing MD trajectories for broader applications in protein engineering, drug discovery, and structural biology.

biophysics↗

bioRxiv2025

Optogenetic control of PLC-γ1 activity polarizes cell motility

Phospholipase C-{gamma}1 (PLC-{gamma}1) signaling is required for mesenchymal chemotaxis, but is it sufficient to bias motility? PLC-{gamma}1 enzyme activity is basally autoinhibited, and light-controlled membrane recruitment of wild-type PLC-{gamma}1 (OptoPLC-{gamma}1) in Plcg1-null fibroblasts does not trigger lipid hydrolysis, complicating efforts to isolate its contribution. Utilizing cancer-associated mutations to investigate the regulatory logic of PLC-{gamma}1, we demonstrate that a hallmark of enzyme activity, phosphorylated Tyr783 (pTyr783), is not a proxy for activity level, but is rather a marker of dysregulated autoinhibition. Accordingly, OptoPLC-{gamma}1 with a deregulating mutation (P867R, S345F, or D1165H) exhibits elevated phosphorylation, and membrane localization of such is sufficient to activate substrate hydrolysis and concomitant motility responses. In particular, local recruitment of OptoPLC-{gamma}1 S345F polarizes cell motility and migration on demand. This response is spatially dose-sensitive and only partially reduced by blocking canonical PLC-{gamma}1 signaling yet is lipase-dependent. Our findings reframe the interpretation of PLC-{gamma}1 regulation and demonstrate that local activation of PLC-{gamma}1 is sufficient to direct cell motility.

cell biology↗

bioRxiv2024

Hyperactive PLCG1 drives non-canonical signaling to promote cell survival

One of the long-standing questions in cell signaling field to identify and characterize key signaling nodes out of a complex network. Phospholipase C{gamma}1 (PLCG1) was identified as the most frequently mutated gene in adult T-cell leukemia/lymphoma, suggesting a critical function of PLCG1 in driving T cell activation. However, it remains unclear how these mutations regulate T cell physiology and pathology. Here we investigated three common leukemia/lymphoma associated mutations (R48W, S345F, and D1165H). We discovered that these mutations induced hyperactive T cell signaling and caused pro-survival phenotypes. PLCG1 mutants enhanced LAT condensation, calcium influx, and ERK activation. They promoted T cell proliferation, induced cell aggregation, and rendered resistance to vorinostat, an FDA-approved drug for cutaneous T-cell lymphoma. The resistance to vorinostat depended on ERK signaling and can be reversed with an ERK inhibitor. Mechanistically, alpha smooth muscle actin, which was specifically induced by PLCG1 mutants, directly bound PLCG1 to promote its activation. Together, these results demonstrated that hyperactive PLCG1 promoted T cell survival and drug resistance through inducing non-canonical signaling.

cell biology↗

bioRxiv2023

De novo design of stable proteins that efficaciously inhibit oncogenic G proteins

Many protein therapeutics are competitive inhibitors that function by binding to endogenous proteins and preventing them from interacting with native partners. One effective strategy for engineering competitive inhibitors is to graft structural motifs from a native partner into a host protein. Here, we develop and experimentally test a computational protocol for embedding binding motifs in de novo designed proteins. The protocol uses an "inside-out" approach: Starting with a structural model of the binding motif docked against the target protein, the de novo protein is built by growing new structural elements off the termini of the binding motif. During backbone assembly, a score function favors backbones that introduce new tertiary contacts within the designed protein and do not introduce clashes with the target binding partner. Final sequences are designed and optimized using the molecular modeling program Rosetta. To test our protocol, we designed small helical proteins to inhibit the interaction between Gq and its effector PLC-{beta} isozymes. Several of the designed proteins remain folded above 90{degrees}C and bind to Gq with equilibrium dissociation constants tighter than 80 nM. In cellular assays with oncogenic variants of Gq, the designed proteins inhibit activation of PLC-{beta} isozymes and Dbl-family RhoGEFs. Our results demonstrate that computational protein design, in combination with motif grafting, can be used to directly generate potent inhibitors without further optimization via high throughput screening or selection. statement for broader audienceEngineered proteins that bind to specific target proteins are useful as research reagents, diagnostics, and therapeutics. We used computational protein design to engineer de novo proteins that bind and competitively inhibit the G protein, Gq, which is an oncogene for uveal melanomas. This computational method is a general approach that should be useful for designing competitive inhibitors against other proteins of interest.

synthetic biology↗

bioRxiv2022

Genetic Variants of Phospholipase C-γ 2 Confer Altered Microglial Phenotypes and Differential Risk for Alzheimers Disease

Genetic association studies have demonstrated the critical involvement of the microglial immune response in Alzheimers disease (AD) pathogenesis. Phospholipase C-gamma-2 (PLCG2) is selectively expressed by microglia and acts in many immune receptor signaling pathways. In AD, PLCG2 is induced uniquely in plaque-associated microglia. A genetic variant of PLCG2, PLCG2P522R, is a mild hypermorph that attenuates AD risk. We report the identification of a PLCG2 variant, PLCG2M28L, associated with loss-of-function and confers increased AD risk. PLCG2P522R attenuates disease in an amyloidogenic murine AD model, whereas PLCG2M28L exacerbates the plaque burden associated with altered phagocytosis and A{beta} clearance. The variants bidirectionally modulate disease pathology by inducing distinct transcriptional programs that identify microglial subpopulations associated with protective or detrimental phenotypes. In summary, these findings identify PLCG2M28L as a new AD risk variant and demonstrate that PLCG2 variants can differentially orchestrate microglial responses in AD pathogenesis that can be therapeutically targeted. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC="FIGDIR/small/519685v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@19f0aa6org.highwire.dtl.DTLVardef@74191eorg.highwire.dtl.DTLVardef@1d3a3forg.highwire.dtl.DTLVardef@db2a44_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIA genetic variant of PLCG2, M28L, is associated with an increased risk for Alzheimers disease (AD) C_LIO_LIIn an amyloidogenic AD mouse model, PLCG2M28L exacerbates disease pathogenesis C_LIO_LIConversely, PLCG2P522R, a protective PLCG2 variant, attenuates AD pathogenesis C_LIO_LIThe PLCG2 variants uniquely alter the microglial transcriptome and phenotypes C_LI

neuroscience↗

bioRxiv2022

Dynamics of allosteric regulation of the phospholipase C-γ isozymes upon recruitment to membranes

Numerous receptor tyrosine kinases and immune receptors activate phospholipase C-gamma (PLC-{gamma}) isozymes at membranes to control diverse cellular processes including phagocytosis, migration, proliferation, and differentiation. The molecular details of this process are not well understood. Using hydrogen-deuterium exchange mass spectrometry (HDX-MS), we show that PLC-{gamma}1 is relatively inert to lipid vesicles that contain its substrate, PIP2, unless first bound to the kinase domain of the fibroblast growth factor receptor (FGFR1). Exchange occurs throughout PLC-{gamma}1 and is exaggerated in PLC-{gamma}1 containing an oncogenic substitution (D1165H) that allosterically activates the lipase. These data support a model whereby initial complex formation shifts the conformational equilibrium of PLC-{gamma}1 to favor activation. This receptor-induced priming of PLC-{gamma}1 also explains the capacity of a kinase-inactive fragment of FGFR1 to modestly enhance the lipase activity of PLC-{gamma}1 operating on lipid vesicles but not a soluble analog of PIP2 and highlights cooperativity between receptor engagement and membrane proximity. Priming is expected to be greatly enhanced for receptors embedded in membranes and nearly universal for the myriad of receptors and co-receptors that bind the PLC-{gamma} isozymes.

biochemistry↗

bioRxiv2020

PLCG2 as a Risk Factor for Alzheimer's Disease

Alzheimers disease (AD) is characterized by robust microgliosis and phenotypic changes that accompany disease pathogenesis. Indeed, genetic variants in microglial genes are linked to risk for AD. Phospholipase C{gamma} 2 (PLCG2) participates in the transduction of signals emanating from immune cell-surface receptors that regulate the inflammatory response and is selectively expressed by microglia in the brain. A rare variant in PLCG2 (P522R) was previously found to be protective against AD, indicating that PLCG2 may play a role in AD pathophysiology. Here, we report that a rare missense variant in PLCG2 confers increased AD risk (p=0.047; OR=1.164 [95% CI=1.002-1.351]). Additionally, we observed that PLCG2 expression levels are increased in several brain regions of AD patients, correlating with brain amyloid deposition. This provides further evidence that PLCG2 may play an important role in AD pathophysiology. Together, our findings indicate that PLCG2 is a potential new therapeutic target for AD.

neuroscience↗

bioRxiv2019

Connectivity analysis of GEF/GTPase networks in living cells

The cytoskeleton is regulated by dynamic, multi-layered signaling networks that interconnect Rho family small GTPases with exquisite spatiotemporal precision1. Understanding the organization of these networks is challenging, as protein activation and interaction occur transiently and with precise subcellular localization. We and others have used fluorescent biosensors in living cells to map the activation patterns of the Rho family small GTPases relative to the changes in cell edge dynamics that they produce2-4. These GTPases are controlled by the localized activity of numerous Rho guanine nucleotide exchange factors (RhoGEFs) with overlapping GTPase specificity5,6. Here we extend this analysis to determine functional relationships between GEFs and GTPases in controlling cell edge movements. First, biosensors for GEF activation are produced, and their activity correlated with edge dynamics. We then shift the wavelengths of GTPase biosensors to image and correlate the activation of GEFs and GTPases in the same cell. Using partial correlation analysis, we can parse out from such multiplexed data the contribution of each GEF - GTPase interaction to edge dynamics, i.e. we identify when and where specific GEF activation events regulate specific downstream GTPases to affect motility. We describe biosensors for eight Dbl family RhoGEFs based on a broadly applicable new design strategy (Asef, Tiam1, Vav isoforms, Tim, LARG, and {beta}-Pix), and red shifted biosensors for RhoA, Rac1 and Cdc42. In the context of motility, functional interactions were identified for Asef regulation of Cdc42 and Rac1. This approach exemplifies a powerful means to elucidate the real-time connectivity of signal transduction networks.

cell biology↗

bioRxiv2018

Lysophosphatidic acid provokes fibroblast chemotaxis through combinatorial regulation of myosin II

Lysophophatidic acid (LPA), a biologically active phospholipid that is ubiquitously present in tissues and organs, provokes cellular responses such as proliferation, apoptosis, differentiation and migration via activation of G-protein coupled receptors. These receptors activate a broad range of intracellular signaling cascades to mediate these responses. Using microfluidic chambers that generate and maintain stable gradients, we observed that chemotaxis of fibroblasts to LPA has higher directional fidelity than chemotaxis provoked by the receptor tyrosine kinase (RTK) ligand platelet-derived growth factor (PDGF). Unlike fast moving amoeboid cells, mesenchymal cells such as fibroblasts do not require PI3K for chemotaxis to a GPCR ligand. In addition, the Arp2/3 complex is not required for fibroblast GPCR-based chemotaxis in either 2D or 3D environments. Our data indicate that combinatorial regulation of myosin II involving global activation by RhoA/ROCK and local inhibition of myosin II at the leading edge by PKC results in highly efficient chemotaxis of fibroblasts to LPA. Based on these observations, we develop a simple mathematical model to explain how dual regulation of myosin II is responsible for enhanced chemotaxis in LPA gradients relative to PDGF. Using pharmacological approaches, we test predictions of this model and modulate the fidelity of LPA and PDGF chemotaxis.

cell biology↗