Biology subjects

Liu, L.

Publications and source records attributed to Liu, L..

At least 829 records · Page 46Linked to original sources

bioRxiv2019

DNA demethylation is a driver for chick retina regeneration

BackgroundA promising avenue toward human retina regeneration lies in identifying the factors that promote cellular reprogramming to retinal neurons in organisms able to undergo retina regeneration. The embryonic chick can regenerate a complete neural retina, after retinectomy, via retinal pigment epithelium (RPE) reprogramming in the presence of FGF2. Cellular reprogramming resets the epigenetic landscape to drive shifts in transcriptional programs and cell identity. Here, we systematically analyzed the reprogramming competent chick RPE prior to injury, and during different stages of reprogramming. We examined the dynamic changes in the levels and distribution of histone marks and DNA modifications, as well as conducted a comprehensive analysis of the DNA methylome during this process.\n\nResultsIn addition to changes in the expression of genes associated with epigenetic modifications during RPE reprogramming, we observed dynamic changes in histone marks and intermediates of the process of DNA demethylation. At early times after injury, H3K27me3 and 5mC repression marks decreased while 5caC and the H3K4me3 activation mark increased, suggesting genome-wide changes in the bivalent chromatin, impaired DNA methylation, and active DNA demethylation in the chromatin reconfiguration of reprogramming RPE. Comprehensive analysis of the methylome by whole-genome bisulfite sequencing (WGBS) confirmed extensive rearrangements of DNA methylation patterns including differentially methylated regions (DMRs) found at promoters of genes associated with chromatin organization and fibroblast growth factor production. In contrast, genes associated with early RPE reprogramming are hypomethylated in the intact RPE and remain hypomethylated during the process. During the generation of a neuroepithelium (NE) at later stages of reprogramming, decreased levels of H3K27me3, 5mC, and 5hmC coincide with elevated levels of H3K27Ac and 5caC, indicating an active demethylation process and genome-wide changes in the active regulatory landscape. Finally, we identify Tet methylcytosine dioxygenase 3 (TET3) as an important factor for DNA demethylation and retina regeneration in the embryonic chick, capable of reprogramming RPE in the absence of exogenous FGF2.\n\nConclusionOur results demonstrated that injury signals early in RPE reprogramming trigger genome-wide dynamic changes in chromatin, including bivalent chromatin and DNA methylation. In the presence of FGF2 these dynamic modifications are further sustained in the commitment to form a new retina. We identify DNA demethylation as a key process driving the process of RPE reprogramming and identified TET3 as a factor able to reprogram RPE in absence of FGF2. Our findings reveal active DNA demethylation as an important process that may be applied to remove the epigenetic barriers in order to regenerate retina in mammals.

developmental biology↗

bioRxiv2019

Regulatory dynamic enzyme-cost flux balance analysis: A unifying framework for constraint-based modeling

Integrated modeling of metabolism and gene regulation continues to be a major challenge in computational biology. While there exist approaches like regulatory flux balance analysis (rFBA), dynamic flux balance analysis (dFBA), resource balance analysis (RBA) or dynamic enzyme-cost flux balance analysis (deFBA) extending classical flux balance analysis (FBA) in various directions, there have been no constraint-based methods so far that allow predicting the dynamics of metabolism taking into account both macromolecule production costs and regulatory events. In this paper, we introduce a new constraint-based modeling framework named regulatory dynamic enzyme-cost flux balance analysis (r-deFBA), which unifies dynamic modeling of metabolism, cellular resource allocation and transcriptional regulation in a hybrid discrete-continuous setting. With r-deFBA, we can predict discrete regulatory states together with the continuous dynamics of reaction fluxes, external substrates, enzymes, and regulatory proteins needed to achieve a cellular objective such as maximizing biomass over a time interval. The dynamic optimization problem underlying r-deFBA can be reformulated as a mixed-integer linear optimization problem, for which there exist efficient solvers.

systems biology↗

bioRxiv2019

Comprehensive molecular characterization of PRKCG for glioma diagnosis, prognosis and treatment prediction

Glioma is one of the most common malignant brain tumors and exhibits low resection rate and high recurrence risk. Although a large number of glioma studies powered by high-throughput sequencing technologies have led to massive multi-omics datasets, there lacks of comprehensive integration of glioma datasets for uncovering candidate biomarker genes. In this study, we collected a large-scale assemble of multi-omics multi-cohort datasets from worldwide public resources, involving a total of 16,939 samples across 19 independent studies. Through comprehensive multi-omics molecular profiling across different datasets, we revealed that PRKCG (Protein Kinase C Gamma), a brain-specific gene detectable in cerebrospinal fluid, is closely associated with glioma. Specifically, it presents lower expression and higher methylation in glioma samples compared with normal samples. PRKCG expression/methylation change from high to low is indicative of glioma progression from low-grade to high-grade and high RNA expression is suggestive of good survival. Importantly, PRKCG in combination with MGMT is effective to predict survival outcomes after TMZ chemotherapy in a more precise manner. Collectively, PRKCG bears the great potential for glioma diagnosis, prognosis and therapy, and PRKCG-like genes may represent a set of important genes associated with different molecular mechanisms in glioma tumorigenesis. Accordingly, our study indicates the importance of computational integrative multi-omics data analysis and represents a data-driven scheme toward precision tumor subtyping and accurate personalized healthcare. Author SummaryGlioma is a type of brain tumors that represents one of the most lethal human malignancies with little chance for recovery. Nowadays, more and more studies have adopted high-throughput sequencing technologies to decode the molecular profiles of glioma from different omics levels, accordingly resulting in massive glioma datasets generated from different projects and laboratories throughout the world. Therefore, it has become crucially important on how to make full use of these valuable datasets for computational identification of glioma candidate biomarker genes in aid of precision tumor subtyping and accurate personalized treatment. In this study, we comprehensively integrated glioma datasets from all over the world and performed multi-omics molecular data mining. We revealed that PRKCG, a brain-specific gene abundantly expressed in cerebrospinal fluid, bears the great potential for glioma diagnosis, prognosis and treatment prediction, which has been consistently observed on multiple independent datasets. In the era of big data, our study highlights the significance of computational integrative data mining toward precision medicine in cancer research.

bioinformatics↗

bioRxiv2019

The maize heterotrimeric G-protein β subunit controls shoot meristem development and immune responses.

Heterotrimeric G-proteins are important transducers of receptor signaling, functioning in plants with CLAVATA receptors in control of shoot meristem size, and with pathogen associated molecular pattern (PAMP) receptors in basal immunity. However, whether specific members of the heterotrimeric complex potentiate crosstalk between development and defense, and the extent to which these functions are conserved across species, has not been addressed. Here we used CRISPR/Cas9 to knockout the maize G{beta} subunit gene, and found that the mutants were lethal, differing from Arabidopsis, where homologous mutants have normal growth and fertility. We show that lethality is not caused by a specific developmental arrest, but by autoimmunity. We used a genetic diversity screen to suppress the lethal g{beta} phenotype, and also identified a new maize G{beta} allele with weak autoimmune responses but strong development phenotypes. Using these tools, we show that G{beta} controls meristem size in maize, acting epistatically with G, suggesting that G{beta} and G function in a common signaling complex. Furthermore, we used an association study to show that natural variation in G{beta} influences maize kernel row number, an important agronomic trait. Our results demonstrate the dual role of G{beta} in immunity and development in a cereal crop, and suggest that it functions in crosstalk between these competing signaling networks. Therefore, modification of G{beta} has the potential to optimize the tradeoff between growth and defense signaling to improve agronomic production.\n\nSignificanceCereal crops, such as maize provide our major food and feed. Crop productivity has been significantly improved by selection of favorable architecture and development alleles, however crops are constantly under attack from pathogens, which severely limits yield due to a defense-growth tradeoff. Therefore, it is critical to identify key signaling regulators that control both developmental and immune signaling, to provide basic knowledge to maximize productivity. This work shows that the maize G protein {beta} subunit regulates both meristem development and immune signaling, and suggests that manipulation of this gene has the potential to optimize the tradeoff between yield and disease resistance to improve crop yields.

plant biology↗

bioRxiv2019

MAGOS: Discovering Subclones in Tumors Sequenced at Standard Depths

Understanding intratumor heterogeneity is critical to designing personalized treatments and improving clinical outcomes of cancers. Such investigations require accurate delineation of the subclonal composition of a tumor, which to date can only be reliably inferred from deep-sequencing data (>300x depth). To enable accurate subclonal discovery in tumors sequenced at standard depths (30-50x), we develop a novel computational method that incorporates an adaptive error model into statistical decomposition of mixed populations, which corrects the mean-variance dependency of sequencing data at the subclonal level. Tested on extensive computer simulations and real-world data, this new method, named model-based adaptive grouping of subclones (MAGOS), consistently outperforms existing methods on minimum sequencing depth, decomposition accuracy and computation efficiency. MAGOS supports subclone analysis using single nucleotide variants and copy number variants from one or more samples of an individual tumor. Applications of MAGOS to whole-exome sequencing data of 331 liver cancer samples discovered a significant association between subclonal diversity and patient overall survival. MAGOS is freely available as an R package at github (https://github.com/liliulab/magos).

bioinformatics↗

bioRxiv2019

High-resolution proteomics identifies potential new markers of Zika and dengue infections

Distinguishing between Zika and dengue virus infections is critical for treatment and anticipation of complications. However, existing biomarkers have high error rates. To identify new potential diagnostic signatures, we used next-generation proteomics to profile 122 serum samples from 62 Zika or dengue patients. We quantified >500 proteins and identified 26 proteins that were significantly differentially expressed. These proteins typically function in infection and wound healing, with several also linked to pregnancy and brain. Integrating machine learning approaches, we used 7 proteins to predict ZIKV infection correctly in 72% of the cases, outperforming other tools. The three most predictive proteins were Platelet Factor 4 Variant 1, Fibrinogen Alpha, and Gelsolin. Finally, we showed that temporal changes in protein signatures from the same patient can disambiguate some diagnoses and serve as indicators for past infections. Taken together, we demonstrate that serum proteomics can be highly valuable to diagnose even challenging samples.

systems biology↗

bioRxiv2019

Nanomorphological and mechanical reconstruction of mesenchymal stem cells during early apoptosis detected by atomic force microscopy

Stem cell apoptosis exists widely in embryonic development, tissue regeneration, repair, aging and pathophysiology of disease. The molecular mechanism of stem cell apoptosis has been extensively investigated. However, alterations in biomechanics and nanomorphology have rarely been studied. Therefore, an apoptosis model was established for bone marrow mesenchymal stem cells (BMSCs) and the reconstruction of the mechanical properties and nanomorphology of the cells were investigated in detail. Atomic force microscopy (AFM), scanning electron microscopy (SEM), laser scanning confocal microscopy (LSCM), flow cytometry and Cell Counting Kit-8 analysis were applied to assess the cellular elasticity modulus, geometry, nanomorphology, cell surface ultrastructure, biological viability and early apoptotic signal (phosphatidylserine, PS). The results indicated that the cellular elastic modulus and volume significantly decreased, whereas the cell surface roughness obviously increased during the first 3 h of cytochalasin B (CB) treatment. Moreover, these alterations preceded the exposure of biological apoptotic signal PS. These findings suggested that cellular mechanical damage is connected with the apoptosis of BMSCs, and the alterations in mechanics and nanomorphology may be a sensitive index to detect alterations in cell viability during apoptosis. The results contribute to a further understanding of the apoptosis from the perspective of cell mechanics.

cell biology↗

bioRxiv2019

Engineering of membrane complex sphingolipids improves osmotic tolerance of Saccharomyces cerevisiae

In order to enhance the growth performance of S. cerevisiae under harsh environmental conditions, mutant XCG001, which tolerates up to 1.5M NaCl, was isolated via adaptive laboratory evolution (ALE). Comparisons made via transcriptome data of XCG001 and the wild-type strain identified ELO2 as being associated with osmotic tolerance. Overexpression of ELO2 increased the contents of inositol phosphorylceramide (IPC, t18:0/26:0), mannosylinositol phosphorylceramide (MIPC, t18:0/22:0(2OH)), MIPC (d18:0/22:0), MIPC (d20:0/24:0), mannosyldiinositol phosphorylceramide (M(IP)2C, d20:0/26:0), M(IP)2C (t18:0/26:0(2OH)) and M(IP)2C (d20:0/26:0(2OH)) by 88.3-, 166.9-, 63.3-, 23.9-, 27.9-, 113.8- and 208.1-fold at 1.0 M NaCl, respectively, compared those of strain XCG002. As a result, membrane integrity, cell growth and cell survival of the ELO2 overexpression strain (XCG010) increased by 24.4%, 29% and 22.1% at 1.0 M NaCl, respectively, compared those of strain XCG002. The findings provided a novel strategy for engineering complex sphingolipids to enhance osmotic tolerance.\n\nIMPORTANCEThis study demonstrated a novel strategy for manipulation membrane complex sphingolipids to enhance S. cerevisiae tolerance to osmotic stress. Osmotic tolerance was related to sphingolipid acyl chain elongase, Elo2, via transcriptome analysis of the wild-type strain and an osmotic tolerant strain generated from ALE. Overexpression of ELO2 increased complex sphingolipid with longer acyl chain, thus improved membrane integrity and osmotic tolerance.

bioengineering↗

bioRxiv2019

Source of additive genetic variance of important traits

Fishers fundamental theorem of natural selection predicts no additive variance of fitness in a natural population. Consistently, observations in a variety of wild populations show virtually no narrow-sense heritability (h2) for traits important to fitness. However, counterexamples are occasionally reported, calling for a deeper understanding on the evolution of additive variance. In this study we propose adaptive divergence followed by population admixture as a source of the additive genetic variance of evolutionarily important traits. We experimentally tested the hypothesis by examining a panel of ~1,000 yeast segregants produced by a hybrid of two yeast strains that experienced adaptive divergence. We measured over 400 yeast cell morphological traits and found a strong positive correlation between h2 and evolutionary importance. Because adaptive divergence followed by population admixture could happen constantly, particularly in some species such as humans, the finding reconciles the observation of abundant additive variances in evolutionarily important traits with Fishers fundamental theorem of natural selection. It also suggests natural selection may effectively promote rather than suppress additive genetic variance in species with wide geographic distribution and strong migratory capacity.

evolutionary biology↗

bioRxiv2019

Lesions of canine prostate underwent laser ablation, radiofrequency ablation, and microwave ablation: Lesions shapes and clinical significances

ObjectiveTo explore the shapes and clinical significances of the lesions of canine prostate underwent laser ablation (LA), radiofrequency ablation (RFA), and microwave ablation (MWA).\n\nMethodsHere, 6 male Beagle dogs were randomly assigned to LA, RFA, and MWA groups, respectively. The ablations were conducted with the doses commonly applied in clinical practice (LA: 3 W/1200 J; RFA and MWA: 30 W/120 s) for one region in the left and right lobes of the prostate, which totally resulted in 12 lesions. An energy transmitter was inserted via the perineum under the guidance of transrectal ultrasound (TRUS) and the ablation process was observed dynamically. After ablation, the efficacy was assessed by contrast-enhanced ultrasonography (CEUS), and transverse diameter (TRD), anteroposterior diameter (APD), and longitudinal diameter (TRD) were measured. Then, the volume (V) was calculated according to the following formulae, V = 1/6 x {pi} x (MLD x APD x LD), and ratio (R) R =[(MLD + APD)/2 x LD], which was used to show the shape of the lesion (The closer R is to 1, the more spherical it is).\n\nResultsThe shapes and sizes of the lesions underwent the three techniques varied under the clinically commonly used doses. The R values, reflecting the changes in shapes of lesions, were 0.89{+/-}0.02, 0.72{+/-}0.01, and 0.65{+/-}0.03 for RFA, MWA, and LA, respectively, which were significantly different (P =0.027). The volumes of the lesions underwent the three ablation techniques significantly varied as well (P=0.001), which were 2.17{+/-}0.10, 1.51{+/-}0.20, and 0.79{+/-}0.07 ml for MWA, LA, and RFA, respectively. Conclusion: The above-mentioned three techniques could be used for ablation of prostate cancer using the clinically commonly used doses. The shapes of the lesions underwent the three ablation techniques varied evidently, with the lesions received RFA and LA were more spherical and oval, respectively, while the shapes of lesions underwent MWA were between spherical and oval. The lesions received MWA and RFA had the largest and smallest sizes, respectively, while sizes of lesions underwent LA were in the middle. These findings may assist physicians to select an appropriate therapeutic method for treatment of prostate disease.

cancer biology↗

bioRxiv2019

Inosine is an alternative carbon supply that supports effector T cell proliferation and anti-tumor function under glucose restriction

T cells undergo a characteristic metabolic rewiring that fulfills the dramatically increased bioenergetic, biosynthetic, and redox demands following antigen stimulation. A robust adaptive immune system requires effector T cells to respond and adapt to fluctuations in environmental nutrient levels imposed by infectious and inflammatory sites in different tissues. Inevitably, such responsiveness and adaptation reflect metabolic plasticity, allowing T cells to elicit immune functions by using a wide range of nutrient substrates. Here, we show that effector T cells utilize inosine, as an alternative substrate, to support cell growth and function in the absence of glucose. T cells metabolize inosine into hypoxanthine and phosphorylated ribose by purine nucleoside phosphorylase (PNP). Using Stable Isotope-Resolved Metabolomics (SIRM), we demonstrated that ribose moiety of inosine can enter into central metabolic pathways to provide ATP and biosynthetic precursors. Accordingly, the dependence of T cells on extracellular glucose for growth and effector functions can be relieved by inosine. On the other hand, cancer cells display diverse capacity to utilize inosine as a carbon resource. Moreover, the supplement of inosine enhances the anti-tumor efficacy of immune-checkpoint blockade or adoptive T cell transfer, reflecting the capability of inosine in relieving tumor-imposed metabolic restrictions on T cells in vivo.

immunology↗

bioRxiv2019

Linked optical and gene expression profiling of single cells at high throughput

Single cell RNA sequencing has emerged as a powerful tool for characterizing cells, but not all phenotypes of interest can be observed through gene expression alone. Linking sequencing with optical analysis has provided insight into the molecular basis behind cellular function, but current approaches have limited throughput. Here, we present a high throughput platform for linked optical and gene expression profiling of single cells. We demonstrate accurate fluorescence and gene expression measurements from thousands of cells in a single experiment and use the platform to characterize DNA and RNA changes in Jurkat cells through the cell cycle. In addition to its scalability, our integration of microfluidics and array-based molecular biology holds promise for comprehensive multi-omics profiling of single cells.

bioengineering↗

bioRxiv2019

Salt-free fractionation of complex isomeric mixtures of glycosaminoglycan oligosaccharides compatible with ESI-MS and microarray analysis

Heparin and heparan sulfate (Hp/HS) are linear complex glycosaminoglycans which are involved in diverse biological processes. The structural complexity brings difficulties in separation, making the study of structure-function relationships challenging. Here we present a separation method for Hp/HS oligosaccharide fractionation with cross-compatible solvent and conditions, combining size exclusion chromatography (SEC), ion-pair reversed phase chromatography (IPRP), and hydrophilic interaction chromatography (HILIC) as three orthogonal separation methods that do not require desalting or extensive sample handling. With this method, the final eluent is suitable for structure-function relationship studies, including tandem mass spectrometry and microarray printing. Our data indicate that high resolution is achieved on both IPRP and HILIC for Hp/HS isomers. In addition, the fractions co-eluted in IPRP could be further separated by HILIC, with both separation dimensions capable of resolving some isomeric oligosaccharides. We demonstrate this method using both unpurified reaction products from isomeric synthetic hexasaccharides and an octasaccharide fraction from enoxaparin, identifying isomers resolved by this multi-dimensional separation method. We demonstrate both structural analysis by MS, as well as functional analysis by microarray printing and screening using a prototypical Hp/HS binding protein: basic-fibroblast growth factor (FGF2). Collectively, this method provides a strategy for efficient Hp/HS structure-function characterization.

biochemistry↗

bioRxiv2019

Dissecting the chitinolytic activity of mammalian chitinases

Chitin is an abundant polysaccharide used by a large range of organisms for structural rigidity and water repulsion. As such, the insoluble crystalline structure of chitin poses significant challenges for enzymatic degradation. Vertebrates do not produce chitin, but do express chitin degrading enzymes. Acidic mammalian chitinase, the primary enzyme involved in the degradation of environmental chitin in mammalian lungs, is a processive glycosyl hydrolase that may be able to make multiple hydrolysis events for each binding event. Mutations to acidic mammalian chitinase have been associated with asthma, and genetic deletion of the enzyme in mice results in significantly increased morbidity and mortality with age. We initially set out to reverse this phenotype by engineering hyperactive acidic mammalian chitinase variants. Using a directed evolution screening approach using commercial fluorogenic substrates, we identified mutations with consistent increases in activity. To determine whether the activity increases observed with oligomeric substrates were consistent with more biologically relevant chitin substrates, we developed new assays to quantify chitinase activity with colloidal crystalline chitin, and identified a high throughput fluorogenic assay that gives sufficient signal to noise advantages to quantify changes to activity due to the addition or removal of a chitin binding domain to the enzyme. We show that the activity increasing mutations derived from our directed evolution screen were lost when crystalline substrates were used. In contrast, naturally occurring gain-of-function mutations gave similar results with oligomeric and crystalline substrates. We also show that the activity differences between acidic mammalian chitinase and chitotriosidase are reduced in the context of crystalline substrate, suggesting that previously reported activity differences with oligomeric substrates may have been largely driven by differential substrate specificity for the oligomers. These results highlight the need for assays against more physiological substrates when engineering complex metabolic enzymes, and provide a new approach that may be broadly applicable to engineering glycosyl hydrolases.

biochemistry↗

bioRxiv2019

Droplet-digital Cas13a assay enables direct single-molecule microRNA quantification

The direct quantification of microRNA at the single-molecule level is still challenging. Herein, we developed a droplet-digital Cas13a assay (ddCA) as a general approach for the amplification-free and absolute quantification of single unlabeled miRNA molecules with single-nucleotide specificity. We demonstrate its simplicity, precise quantification capability, excellent specificity and broad applicability by analyzing microRNAs from synthetic and cell lines-derived materials.

biochemistry↗

bioRxiv2019

Enzyme-free synthesis of natural phospholipids in water

All living organisms synthesize phospholipids as the primary constituent of their cell membranes. While phospholipids can spontaneously self-assemble in water to form membrane-bound vesicles, their aqueous synthesis requires pre-existing membrane-embedded enzymes. This limitation has led to models in which the first cells used simpler types of membrane building blocks and has hampered integration of phospholipid synthesis into artificial cells. Here we demonstrate that a combination of ion pairing and self-assembly of reactants allows high-yielding synthesis of cellular phospholipids in water. Acylation of 2-lysophospholipids using cationic thioesters occurs in mildly alkaline solutions resulting in the formation of cell-like membranes. A variety of membrane-forming natural phospholipids can be synthesized. Membrane formation takes place in water from natural alkaline sources, such as soda lakes and hydrothermal oceanic vents. When formed vesicles are transferred to more acidic solutions, electrochemical proton gradients are spontaneously established and maintained.

biochemistry↗

bioRxiv2019

Mutational signatures in upper tract urothelial carcinoma define etiologically distinct subtypes with prognostic relevance

Parts of East Asia have a very high upper tract urothelial carcinoma (UTUC) prevalence, and an etiological link between the medicinal use of herbs containing aristolochic acid (AA) and UTUC has been established. The mutational signature of AA, which is characterized by a particular pattern of A:T to T:A transversions, can be detected by genome sequencing. Thus, integrating mutational signatures analysis with clinicopathological data may be a crucial step toward personalized treatment strategies for the disease. Therefore, we performed whole-genome sequencing (WGS) of 90 UTUC patients from China. Mutational signature analysis via nonnegative matrix factorization method defined three etiologically distinct subtypes with prognostic relevance: (i) AA, the typical AA mutational signature characterized by signature 22, had the highest tumor mutation burden, the best clinical outcomes; (ii) Age, an age-related group featured by signatures 1 and 5, had the lowest weighted genome instability index score, the worst clinical outcomes; and (iii) DSB, signature with deficiencies in DNA double strand break-repair featured by signatures 3, the intermediate clinical outcomes. Additionally, the distinct AA subtype was associated with AA exposure, the highest number of predicted neoantigens and heavier lymphocytes infiltrating. Thus, it may be good candidate for immune checkpoint blockade therapy. Notably, we showed AA-mutational signature was also identified in histologically \"normal\" urothelial cells. Thus, non-invasive urine test based on the AA-mutational signature could take advantage of this \"field effect\" to screen individuals at increased risk of recurrence due to exposure to herbal remedies containing the carcinogen AA. Collectively, the findings here may accelerate the development of novel prognostic markers and personalized therapeutic approaches for UTUC patients in China.

genomics↗

bioRxiv2019

The effects of terminal tagging on homomeric interactions of the sigma 1 receptor

The sigma 1 receptor ({sigma}1R) has been implicated in cancers, neurological disorders, and substance use disorders. Yet, its molecular and cellular functions have not been well-understood. Recent crystal structures of {sigma}1R reveal a single N-terminal transmembrane segment and C-terminal ligand-binding domain, and a trimeric organization. Nevertheless, outstanding issues surrounding the functional or pharmacological relevance of {sigma}1R oligomerization remain, such as the minimal protomeric unit and the differentially altered oligomerization states by different classes of ligands. Western blot (WB) assays have been widely used to investigate protein oligomerizations. However, the unique topology of {sigma}1R renders several intertwined challenges in WB. Here we describe a WB protocol without temperature denaturization to study the ligand binding effects on the oligomerization state of {sigma}1R. Using this approach, we observed unexpected ladder-like incremental migration pattern of {sigma}1R, demonstrating preserved homomeric interactions in the detergent environment. We compared the migration patterns of intact {sigma}1R construct and the C-terminally tagged {sigma}1R constructs, and found similar trends in response to drug treatments. In contrast, N-terminally tagged {sigma}1R constructs show opposite trends to that of the intact construct, suggesting distorted elicitation of the ligand binding effects on oligomerization. Together, our findings indicate that the N-terminus plays an important role in eliciting the impacts of bound ligands, whereas the C-terminus is amenable for modifications for biochemical studies.

biochemistry↗