Biology subjects

Shuken, S. R.

Publications and source records attributed to Shuken, S. R..

8 recordsLinked to original sources

bioRxiv2026

Multi-omic characterization of axolotl perilymph-cerebrospinal fluid reveals shifts in composition during limb regeneration

The axolotl salamander can fully regenerate amputated limbs, yet the systemic consequences underlying this process remain largely understudied. Cerebrospinal fluid is an emerging signaling medium capable of communicating with both the central and peripheral nervous systems, but its composition and potential role in salamander limb regeneration have not yet been examined using modern multi-omics techniques. Here, we developed a protocol for extracting mixed perilymph-cerebrospinal fluid (P-CSF) from axolotl and provided the first proteomic and metabolomic characterization of this biological fluid. We identified 2,626 unique proteins and 173 high-confidence metabolites and quantified them across four time points of early limb regeneration. We demonstrated that limb amputation drives progressive shifts in P-CSF proteins, including an elevation of sarcomeric muscle proteins, regeneration-associated factors, and protease/extracellular matrix proteins. We observed shifts in metabolites involved in oxidative stress, polyunsaturated fatty acid oxidation, and histamine metabolism. Injury-comparison experiments revealed that the observed proteomic changes as a result of limb amputation are different than crush injury, denervation, or tail amputation. This study proposes axolotl P-CSF as a reservoir for limb amputation-associated systemic signaling and as a potential conduit of signals involved in limb regeneration.

systems biology↗

bioRxiv2026

High Resolution Multi-Pass Astral Analyzer Quantification Enables Highly Multiplexed 35-Plex Tandem Mass Tag Proteomics

Tandem mass tags (TMT) allow highly multiplexed and thus high-throughput, precisely quantitative proteomic analysis. Incorporation of additional deuterated reporter channels has near-doubled the multiplexation achieved with Thermo Scientific TMTpro reagents from 18 to 35-plex but requires extremely high [~]100k analyzer resolving power at m/z 128 to differentiate and quantify reporter ion channels, far beyond any single reflection time-of-flight analyzer, and exceeding the multi-reflection Thermo Scientific Astral analyzer in its standard operation. A multi-pass mode of Astral operation has been developed for the Thermo Scientific Orbitrap Astral Zoom mass spectrometer that triples the ion path to 90 m, more than doubling resolving power for a narrow m/z range. This "TMT HR mode" has been integrated into a new method of TMT proteomic analysis that splits regular MS2 analysis of labeled peptides into paired measurements comprising wide mass range scans for peptide identification, and TMT HR mode scans for reporter ion quantification. The method has been shown to accurately quantify 32-plex labeled HeLa protein lysate and provide far greater depth of analysis as state-of-the-art Orbitrap-only methods, while analysis of 11-plex labeled yeast showed no analytical depth sacrificed vs regular Orbitrap Astral TMT analysis. Further comparative measurements of a 2-cell line 35-plex sample demonstrated greater analytical depth, and similar quantitative precision, to "gold standard" Orbitrap MS3 methods.

biochemistry↗

bioRxiv2025

Next-Generation Multiplexed Targeted Proteomics Quantifies Post-Translational Modifications, Compound-Protein Interactions, and Disease Biomarkers with High Throughput

The GoDig platform enables sensitive, multiplexed targeted pathway proteomics without manual scheduling or synthetic standards. Here we present GoDig 2.0, which increases sample multiplexing to 35-fold, improves time efficiency and reduces scan delays for higher success rates, and allows flexible spectral and elution library generation from different mass spectrometry data types. GoDig 2.0 measures 2.4x more targets than GoDig 1.0, quantifying >99% of 800 peptides in a single run. We compiled a library of 23,989 human phosphorylation sites from a phosphoproteomic dataset and used it to profile kinase signaling differences across cell lines. In human brain tissue, we established a hyperphosphorylated tau assay including pTau127, revealing potential biomarkers for Alzheimers disease. We also quantified diglycyl-lysine peptides to assess polyubiquitin branching. Finally, we built a library of 20,946 reactive cysteines and profiled covalent compound-protein interactions spanning diverse pathways. GoDig 2.0 enables high-throughput analyses of site-specific protein modifications across many biological contexts.

biochemistry↗

bioRxiv2025

Library-Free Multiplexed Targeted Proteomics Enables Quantitative Protein-Level Genotyping

Existing targeted mass spectrometry methods require synthetic standard peptides, manual scan scheduling, or data libraries to quantify target proteins. Here we present GoDig-LiF, which uses spectra and retention times predicted by the Prosit-TMT model in place of data libraries, enabling targeted proteomics with only a tandem mass tag-labeled sample, target list, and mass spectrometer. We applied GoDig-LiF to the quantification of mutated proteins in cancer cell lines, including KRAS G13D.

bioinformatics↗

bioRxiv2025

Cell-surface proteomic profiling identifies CD72 as a regulator of microglial tiling

Microglial tiling--the phenomenon of consistent cell-to-cell distances and non-overlapping processes--is regarded as a qualitative indicator of homeostasis, but mechanisms of microglial tiling are unknown. We used cell-surface proximity labeling and mass spectrometry to profile the microglial cell-surface proteome in an in vitro model of homeostatic glial physiology and used single-cell RNA sequencing and public databases to identify candidate cell-surface proteins that might modulate tiling. We designed an image-based functional assay which measures six morphological/spatial readouts to screen these proteins for modulation of tiling. CD72, a coreceptor to the B cell receptor that is expressed by microglia, disrupted tiling; we validated its effects in vitro and in situ in organotypic hippocampal brain slices. Phosphoproteomic studies revealed that CD72 modulates pathways associated with cell adhesion, repulsive receptors, microglial activation, and cytoskeletal organization. These results lay the groundwork for further investigation of the functional roles of tiling in homeostasis and disease.

neuroscience↗

bioRxiv2024

Circulatory proteins shape microglia state and boost phagocytosis

Microglia, the brains immune cells, are highly responsive to their local environment. Given that circulatory proteins can enter the brain, we asked whether microglia are responsive to such proteins. Here, we identify a stable population of microglia specialized to take up circulatory proteins in a region-specific manner under physiological conditions; human hematopoietic stem cell-derived microglia replacing endogenous microglia in chimeric mice show similar regional specialization. Plasma-positive microglia are characterized by prominent expression of genes related to innate immunity and antigen presentation and exhibit high metabolic and phagocytic activity. This activity is dependent, in part, on microglial uptake and accumulation of circulatory Apolipoprotein AI (ApoA-I). Our findings thus identify a new model of communication between brain and periphery through specialized microglia.

neuroscience↗

bioRxiv2024

Inserting Pre-Analytical Chromatographic Priming Runs Significantly Improves Targeted Pathway Proteomics With Sample Multiplexing

GoDig, a recent platform for targeted pathway proteomics without the need for manual assay scheduling or synthetic standard peptides, is a relatively flexible and easy-to-use method that uses tandem mass tags (TMT) to increase sample throughput up to 18-fold relative to label-free targeted proteomics. Though the protein quantification success rate of GoDig is generally high, the peptide-level success rate is more limited, hampering the extension of GoDig to assays of harder-to-quantify proteins and site-specific phenomena. In order to guide the optimization of GoDig assays as well as improvements to the GoDig platform, we created GoDigViewer, a new stand-alone software that provides detailed visualizations of GoDig runs. GoDigViewer guided the implementation of "priming runs," an acquisition mode with significantly higher success rates due to improved elution order calibration. In this mode, one or more chromatographic priming runs are automatically performed to determine accurate and precise target elution orders, followed by analytical runs which quantify targets. Using priming runs, peptide-level quantification success rates exceeded 97% for a list of 400 peptide targets and 95% for a list of 200 targets that are usually not quantified using untargeted mass spectrometry. We used priming runs to establish a quantitative assay of 125 macroautophagy proteins that had a >95% success rate and revealed differences in macroautophagy protein expression profiles across four human cell lines.

cell biology↗

bioRxiv2021

Visualizing the Costs and Benefits of Correcting P-Values for Multiple Hypothesis Testing in Omics Data

The multiple hypothesis testing problem is inherent in high-throughput quantitative genomic, transcriptomic, proteomic, and other "omic" screens. The correction of p-values for multiple testing is a critical element of quantitative omic data analysis, yet many researchers are unfamiliar with the sensitivity costs and false discovery rate (FDR) benefits of p-value correction. We developed models of quantitative omic experiments, modeled the costs and benefits of p-value correction, and visualized the results with color-coded volcano plots. We developed an R Shiny web application for further exploration of these models which we call the Simulator of P-value Multiple Hypothesis Correction (SIMPLYCORRECT). We modeled experiments in which no analytes were truly differential between the control and test group (all null hypotheses true), all analytes were differential, or a mixture of differential and non-differential analytes were present. We corrected p-values using the Benjamini-Hochberg (BH), Bonferroni, and permutation FDR methods and compared the costs and benefits of each. By manipulating variables in the models, we demonstrated that increasing sample size or decreasing variability can reduce or eliminate the sensitivity cost of p-value correction and that permutation FDR correction can yield more hits than BH-adjusted and even unadjusted p-values in strongly differential data. SIMPLYCORRECT can serve as a tool in education and research to show how p-value adjustment and various parameters affect the results of quantitative omics experiments.

bioinformatics↗