Biology subjects

Chen, Z.-L.

Publications and source records attributed to Chen, Z.-L..

8 recordsLinked to original sources

bioRxiv2025

Improved identification of peptides, cross-link sites, and modification sites by Target-enhanced Accurate Inclusion Mass Screening (TAlMS)

Chemical cross-linking of proteins coupled with mass spectrometry provides structural insights by identifying cross-linked peptide pairs, abbreviated as cross-links. Presently, cross-link identification suffers from ambiguity and poor sensitivity, because they are typically of lower abundance and consequently of lower MS2 quality than linear peptides present in the same sample. Here, we present Target-enhanced Accurate Inclusion Mass Screening (TAIMS), a meticulously optimized targeted mass spectrometry method. TAIMS significantly improved the quality of MS2 as indicated by fragment ion coverage (FIC) and other metrics. From data-dependent acquisition (DDA) to TAIMS, high-FIC cross-links increased by 401 or 678 on yeast ribosome or E. coli lysate, respectively, or from about 40% to around 90%. As a result, TAIMS substantially enhanced the accuracy of cross-link site localization and mitigated sensitivity loss in cross-link identification from large database searches. Enhanced identification sensitivity of TAIMS is further evidenced by its capacity to recover genuine cross-link identifications from data that would typically be discarded. On cross-linked E. coli lysate, 10.5% (284/2711) of the inclusion-list entries generated from unidentified cross-link-spectrum matches gained identity through TAIMS. Of these, 230 were linear peptides and 54 were cross-links, including 10 inter-molecular cross-links missed entirely by DDA. Additionally, we demonstrate that TAIMS is a general method for identification of low-abundance, post-translationally modified peptides. On a mouse brain sample, TAIMS increased the number of phosphopeptides identified with accurate phosphosite assignment by 67%. These findings indicate that TAIMS holds broad applicability in proteomics.

biochemistry↗

bioRxiv2024

Global analysis of protein and small-molecule substrates of ubiquitin-like proteins (UBLs)

AbstractUbiquitin-like proteins (UBLs) constitute a family of evolutionarily conserved proteins that share similarities with ubiquitin in 3D structures and modification mechanisms. For most UBLs including Small-Ubiquitin-like Modifiers (SUMO), their modification sites on substrate proteins cannot be identified using the mass spectrometry-based method that has been successful for identifying ubiquitination sites, unless a UBL protein is mutated accordingly. To identify UBL modification sites without having to mutate UBL, we have developed a dedicated search engine pLink-UBL on the basis of pLink, a software tool for identification of cross-linked peptide pairs. pLink-UBL exhibited superior precision, sensitivity, and speed than "make-do" search engines such as MaxQuant, pFind, and pLink. For example, compared to MaxQuant, pLink-UBL increased the number of identified SUMOylation sites by 50 [~] 300% from the same datasets. Additionally, we present a method for identifying small-molecule modifications of UBLs. This method involves antibody enrichment of a UBL C-terminal peptide following enrichment of a UBL protein, followed by LC-MS/MS analysis and a pFind 3 blind search to identify unexpected modifications. Using this method, we have discovered non-protein substrates of SUMO, of which spermidine is the major one for fission yeast SUMO Pmt3. Spermidine can be conjugated to the C-terminal carboxylate group of Pmt3 through its N1 or also likely, N8 amino group in the presence of SUMO E1, E2, and ATP. Pmt3-spermidine conjugation does not require E3 and can be reversed by SUMO isopeptidase Ulp1. SUMO-spermidine conjugation is present in mice and humans. Also, spermidine can be conjugated to ubiquitin in vitro by E1 and E2 in the presence of ATP. The above observations suggest that spermidine may be a common small molecule substrate of SUMO and possibly ubiquitin across eukaryotic species. HighlightsO_LIA specialized software pLink-UBL enables precise identification of UBL modification sites on protein substrates. C_LIO_LIpFind 3 blind search enables identification of unexpected small-molecule substrates of a UBL protein. C_LIO_LISpermidine is a small molecule substrate of fission yeast SUMO Pmt3 as well as mammalian SUMO proteins. C_LIO_LIThe C-terminal carboxyl group of Pmt3 can be attached to the N1 or likely also the N8 amino group of spermidine in the presence of E1, E2, and ATP, and can be detached by SUMO isopeptidase. C_LI

biochemistry↗

bioRxiv2024

Enhancing Phylogenetic Analysis: Integrating Nonparametric Methods for Addressing Abrupt Evolutionary Shifts

Traditional phylogenetically aware correlation methods perform well under gradual evolutionary processes. However, abrupt evolutionary shifts--or macroevolutionary jumps, characteristic of punctuated evolution--can produce extreme phylogenetically independent contrasts (PIC), leading to inflated false positives or increased false negatives in trait correlation analyses. We introduce O(D)GC (Outlier-and Distribution-Guided Correlation), a flexible workflow that identifies outliers in PICs using a distribution-free boxplot criterion and applies Spearman correlation whenever influential outliers are detected. If no outliers are detected, Pearson correlation is used--automatically for large datasets (n [≥] 30), or guided by normality testing in smaller samples. We systematically compared PIC-O(D)GC with five widely applied phylogenetic correlation methods--PIC-Pearson, PIC-MM, PGLS (phylogenetic generalized least squares), MR-PMM (multi-response phylogenetic mixed model), and Corphylo--on 322,000 simulated datasets spanning five evolutionary scenarios (two shift settings: single-trait shifts and dual-trait co-directional jumps; and three no-shift gradual evolution settings), including both fixed-depth and randomly located shifts, tested across 11 shift or noise gradients, three tree sizes (16, 128, 256 tips), and both balanced and random topologies. Overall, PIC-O(D)GC achieved error rates comparable to--or noticeably higher than--those of PIC-MM, while yielding substantially lower error rates than most alternative methods. Under no-shift conditions, it retained power similar to other methods. Analyses of three empirical datasets likewise showed that PIC-O(D)GC and PIC-MM corrected shift-induced distortions that misled conventional methods. Moreover, PIC-O(D)GC offers a conceptually simple framework and incurs markedly lower computational cost. By design, its correlation-only output provides less mechanistic detail than regression-based approaches like PGLS. However, when paired with PIC diagnostics, this outlier-guided strategy highlights evolutionary jumps, distinguishes coupled from decoupled shifts, and--via clade partitioning or tip pruning--recovers background correlations, offering biologically informative insights into how punctuated events interact with gradual trends in trait evolution.

evolutionary biology↗

bioRxiv2024

Exploring Dependent Variable Selection in Phylogenetic Eigenvector Regression

Phylogenetic eigenvector regression (PVR) is widely used in ecology and evolution by representing phylogenetic structure through separable eigenvectors. Despite this flexibility, its implementation faces three key challenges: (1) the selection of eigenvectors, (2) the reduced robustness of ordinary least-squares (OLS) regression under shift-like evolutionary heterogeneity, and (3) the applicability of conventional model complexity rules such as the "samples-per-variable (SPV) [≥] 10" guideline. Here, we propose an optimized PVR framework that addresses these limitations. First, we show that trait-specific selections of eigenvectors often diverge, sometimes producing inconsistent results, and that using their union offers stronger control of phylogenetic non-independence. Second, we evaluate robust regression estimators within PVR, demonstrating that PVR-MM - and in most cases PVR-L2, the standard OLS estimator - maintains high accuracy under non-stationary evolutionary shifts where other non-robust methods fail. Third, through simulation, we reassess the SPV [≥] 10 rule, showing that PVR tolerates eigenvector counts well beyond this threshold, offering greater flexibility while requiring attention to potential overfitting. Extensive simulations across diverse trees and evolutionary scenarios confirm that the optimized framework improves accuracy and robustness. By addressing key aspects of eigenvector selection, regression, and model complexity, our findings strengthen the reliability and applicability of PVR.

evolutionary biology↗

bioRxiv2024

Lecanemab Blocks the Effects of the Aβ/Fibrinogen Complex on Blood Clots and Synapse Toxicity in Organotypic Culture

Proteinaceous brain inclusions, neuroinflammation, and vascular dysfunction are common pathologies in Alzheimers disease (AD). Vascular deficits include a compromised blood-brain barrier, which can lead to extravasation of blood proteins like fibrinogen into the brain. Fibrinogens interaction with the amyloid-beta (A{beta}) peptide is known to worsen thrombotic and cerebrovascular pathways in AD. Lecanemab, an FDA-approved antibody therapy for AD, shows promising results in facilitating reduction of A{beta} from the brain and slowing cognitive decline. Here we show that lecanemab blocks fibrinogens binding to A{beta} protofibrils, normalizing A{beta}/fibrinogen-mediated delayed fibrinolysis and clot abnormalities in vitro and in human plasma. Additionally, we show that lecanemab dissociates the A{beta}/fibrinogen complex and prevents fibrinogen from exacerbating A{beta}-induced synaptotoxicity in mouse organotypic hippocampal cultures. These findings reveal a possible protective mechanism by which lecanemab may slow disease progression in AD.

biochemistry↗

bioRxiv2023

Which Variable Should Be Dependent in Phylogenetic Generalized Least Squares Regression Analysis

Phylogenetic generalized least squares (PGLS) regression is widely used to examine evolutionary associations while accounting for phylogenetic non-independence, but it requires designating one trait as the dependent variable and the other as the independent variable. When causal relationships between traits are unclear, choosing which trait serves as the dependent variable becomes a practical concern. While studying the evolutionary relationship between bacterial growth rate and CRISPR-Cas content, we noticed that switching the roles of dependent and independent variables in PGLS analyses could lead to inconsistent conclusions in a substantial proportion of cases. To confirm this observation, we conducted 16,000 simulations of trait evolution along binary trees with 100 terminal nodes under different evolutionary models. PGLS regressions using Pagels {lambda} model were applied to each simulation, and the results consistently showed that swapping the dependent and independent variables can lead to inconsistent outcomes. We evaluated seven potential criteria for selecting the dependent variable, including log-likelihood, AIC, R2, p-value, Pagels {lambda}, Blombergs K, and the estimated {lambda} in the Pagels {lambda} model. Among these, Pagels {lambda}, Blombergs K, and the estimated {lambda} performed equally well and outperformed the others in selecting the dependent variable, providing a reliable basis for PGLS analyses when causal direction between traits is unclear.

evolutionary biology↗

bioRxiv2018

Corilagin controls post-parasiticide schistosome egg-induced liver fibrosis by inhibiting Stat6 signalling pathway

This study aims to explore the effect of Corilagin (Cor) on post-parasiticide schistosome egg-induced hepatic fibrosis through the Stat6 signalling pathway in vitro and in vivo. Cellular and animal models were established and treated by Corilagin. The inhibitory effect of Corilagin was also confirmed in RAW264.7 cells in which Stat6 was overexpressed based on the GV367-Stat6-EGFP lentiviral vector system and in which Stat6 was knock-downed by gene specific siRNAs. As a result, Corilagin prevented increases in the protein level of Phospho-Stat6 (P-Stat6). Both the mRNA and protein levels of the downstream mediators SOCS1, KLF4, and PPAR{gamma}/{delta} were markedly suppressed after Corilagin treatment. Expression of ARG1 and FIZZ1/Retnla, Ym1, TGF-{beta} and PDGF in serum were also inhibited by Corilagin. The pathological changes, area of granulomas of liver sections, and degree of hepatic fibrosis were significantly alleviated in the Corilagin group. The areas of CD68- and CD206-positive cells stained by immunofluorescence were significantly decreased by Corilagin. In conclusion, Corilagin can suppress post-parasiticide schistosome egg-induced hepatic fibrosis by inhibiting the Stat6 signalling pathway and provide a new therapeutic strategy for schistosomiasis liver fibrosis.

pharmacology and toxicology↗

bioRxiv2018

Open-pFind enables precise, comprehensive and rapid peptide identification in shotgun proteomics

Shotgun proteomics has grown rapidly in recent decades, but a large fraction of tandem mass spectrometry (MS/MS) data in shotgun proteomics are not successfully identified. We have developed a novel database search algorithm, Open-pFind, to efficiently identify peptides even in an ultra-large search space which takes into account unexpected modifications, amino acid mutations, semi- or non-specific digestion and co-eluting peptides. Tested on two metabolically labeled MS/MS datasets, Open-pFind reported 50.5-117.0% more peptide-spectrum matches (PSMs) than the seven other advanced algorithms. More importantly, the Open-pFind results were more credible judged by the verification experiments using stable isotopic labeling. Tested on four additional large-scale datasets, 70-85% of the spectra were confidently identified, and high-quality spectra were nearly completely interpreted by Open-pFind. Further, Open-pFind was over 40 times faster than the other three open search algorithms and 2-3 times faster than three restricted search algorithms. Re-analysis of an entire human proteome dataset consisting of [~]25 million spectra using Open-pFind identified a total of 14,064 proteins encoded by 12,723 genes by requiring at least two uniquely identified peptides. In this search results, Open-pFind also excelled in an independent test for false positives based on the presence or absence of olfactory receptors. Thus, a practical use of the open search strategy has been realized by Open-pFind for the truly global-scale proteomics experiments of today and in the future.

bioinformatics↗