Cell-type-specific transcriptomics uncovers spatial regulatory networks in bioenergy sorghum stems.

Bioenergy sorghum is a low-input, drought-resilient, deep-rooting annual crop that has high biomass yield potential enabling the sustainable production of biofuels, biopower, and bioproducts. Bioenergy sorghum's 4-5 m stems account for ~80% of the harvested biomass. Stems accumulate high levels of sucrose that could be used to synthesize bioethanol and useful biopolymers if information about cell-type gene expression and regulation in stems was available to enable engineering. To obtain this information, laser capture microdissection was used to isolate and collect transcriptome profiles from five major cell types that are present in stems of the sweet sorghum Wray. Transcriptome analysis identified genes with cell-type-specific and cell-preferred expression patterns that reflect the distinct metabolic, transport, and regulatory functions of each cell type. Analysis of cell-type-specific gene regulatory networks (GRNs) revealed that unique transcription factor families contribute to distinct regulatory landscapes, where regulation is organized through various modes and identifiable network motifs. Cell-specific transcriptome data was combined with known secondary cell wall (SCW) networks to identify the GRNs that differentially activate SCW formation in vascular sclerenchyma and epidermal cells. The spatial transcriptomic dataset provides a valuable source of information about the function of different sorghum cell types and GRNs that will enable the engineering of bioenergy sorghum stems, and an interactive web application developed during this project will allow easy access and exploration of the data (https://mc-lab.shinyapps.io/lcm-dataset/).

In-Depth Proteome Profiling of Small Extracellular Vesicles Isolated from Cancer Cell Lines and Patient Serum.

Extracellular vesicle (EV) secretion has been observed in many types of both normal and tumor cells. EVs contain a variety of distinctive cargoes, allowing tumor-derived serum proteins in EVs to act as a minimally invasive method for clinical monitoring. We have undertaken a comprehensive study of the protein content of the EVs from several cancer cell lines using direct data-independent analysis. Several thousand proteins were detected, including many classic EV markers such as CD9, CD81, CD63, TSG101, and Syndecan-1, among others. We detected many distinctive cancer-specific proteins, including several known markers used in cancer detection and monitoring. We further studied the protein content of EVs from patient serum for both normal controls and pancreatic cancer and hepatocellular carcinoma. The EVs for these studies have been isolated by various methods for comparison, including ultracentrifugation and CD9 immunoaffinity column. Typically, 500-1000 proteins were identified, where most of them overlapped with the EV proteins identified from the cell lines studied. We were able to identify many of the cell-line EV protein markers in the serum EVs, in addition to the large numbers of proteins specific to pancreatic and HCC cancers.

Distinctive carbon repression effects in the carbohydrate-selective wood decay fungus Rhodonia placenta.

Brown rot fungi dominate the carbon degradation of northern terrestrial conifers. These fungi adapted unique genetic inventories to degrade lignocellulose and to rapidly release a large quantity of carbohydrates for fungal catabolism. We know that brown rot involves "two-step" gene regulation to delay most hydrolytic enzyme expression until after harsh oxidative pretreatments. This implies the crucial role of concise gene regulation to brown rot efficacy, but the underlying regulatory mechanisms remain uncharacterized. Here, using the combined transcriptomic and enzyme analyses we investigated the roles of carbon catabolites in controlling gene expression in model brown rot fungus Rhodonia placenta. We identified co-regulated gene regulons as shared transcriptional responses to no-carbon controls, glucose, cellobiose, or aspen wood (Populus sp.). We found that cellobiose, a common inducing catabolite for fungi, induced expression of main chain-cleaving cellulases in GH5 and GH12 families (cellobiose vs. no-carbon > 4-fold, Padj < 0.05), whereas complex aspen was a universal inducer for Carbohydrate Active Enzymes (CAZymes) expression. Importantly, we observed the attenuated glucose-mediated repression effects on cellulases expression, but not on hemicellulases and lignin oxidoreductases, suggesting fungi might have adapted diverged regulatory routes to boost cellulase production for the fast carbohydrate release. Using carbon regulons, we further predicted the cis- and trans-regulatory elements and assembled a network model of the distinctive regulatory machinery of brown rot. These results offer mechanistic insights into the energy efficiency traits of a common group of decomposer fungi with enormous influence on the carbon cycle.

Capturing an Early Gene Induction Event during Wood Decay by the Brown Rot Fungus Rhodonia placenta.

Brown rot fungi dominate wood decomposition in coniferous forests, and their carbohydrate-selective mechanisms are of commercial interest. Brown rot was recently described as a two-step, sequential mechanism orchestrated by fungi using differentially expressed genes (DEGs) and consisting of oxidation via reactive oxygen species (ROS) followed by enzymatic saccharification. There have been indications, however, that the initial oxidation step itself might require induction. To capture this early gene regulation event, here, we integrated fine-scale cryosectioning with whole-transcriptome sequencing to dissect gene expression at the single-hyphal-cell scale (tens of micrometers). This improved the spatial resolution 50-fold, relative to previous work, and we were able to capture the activity of the first 100 µm of hyphal front growth by Rhodonia placenta in aspen wood. This early decay period was dominated by delayed gene expression patterns as the fungus ramped up its mechanism. These delayed DEGs included many genes implicated in ROS pathways (lignocellulose oxidation [LOX]) that were previously and incorrectly assumed to be constitutively expressed. These delayed DEGs, which include those with and without predicted functions, also create a focused subset of target genes for functional genomics. However, this delayed pattern was not universal, with a few genes being upregulated immediately at the hyphal front. Most notably, this included a gene commonly implicated in hydroquinone and iron redox cycling: benzoquinone reductase. IMPORTANCE Earth's aboveground terrestrial biomass is primarily wood, and fungi dominate wood decomposition. Here, we studied these fungal pathways in a common "brown rot"-type fungus, Rhodonia placenta, that selectively extracts sugars from carbohydrates embedded within wood lignin. Using a space-for-time design to map fungal gene expression at the extreme hyphal front in wood, we made two discoveries. First, we found that many genes long assumed to be "on" (constitutively expressed) from the very beginning of decay were instead "off" before being upregulated, when mapped (via transcriptome sequencing [RNA-seq]) at a high resolution. Second, we found that the gene encoding benzoquinone reductase was "on" in incipient decay and quickly downregulated, implying a key role in "kick-starting" brown rot.

Characterization of cellular oxidative stress response by stoichiometric redox proteomics.

The thiol redox proteome refers to all proteins whose cysteine thiols are subjected to various redox-dependent posttranslational modifications (PTMs) including S-glutathionylation (SSG), S-nitrosylation (SNO), S-sulfenylation (SOH), and S-sulfhydration (SSH). These modifications can impact various aspects of protein function such as activity, binding, conformation, localization, and interactions with other molecules. To identify novel redox proteins in signaling and regulation, it is highly desirable to have robust redox proteomics methods that can provide global, site-specific, and stoichiometric quantification of redox PTMs. Mass spectrometry (MS)-based redox proteomics has emerged as the primary platform for broad characterization of thiol PTMs in cells and tissues. Herein, we review recent advances in MS-based redox proteomics approaches for quantitative profiling of redox PTMs at physiological or oxidative stress conditions and highlight some recent applications. Considering the relative maturity of available methods, emphasis will be on two types of modifications: 1) total oxidation (i.e., all reversible thiol modifications), the level of which represents the overall redox state, and 2) S-glutathionylation, a major form of reversible thiol oxidation. We also discuss the significance of stoichiometric measurements of thiol PTMs as well as future perspectives toward a better understanding of cellular redox regulatory networks in cells and tissues.

Comprehensive Detection of Single Amino Acid Variants and Evaluation of Their Deleterious Potential in a PANC-1 Cell Line.

Identifying single amino acid variants (SAAVs) in cancer is critical for precision oncology. Several advanced algorithms are now available to identify SAAVs, but attempts to combine different algorithms and optimize them on large data sets to achieve a more comprehensive coverage of SAAVs have not been implemented. Herein, we report an expanded detection of SAAVs in the PANC-1 cell line using three different strategies, which results in the identification of 540 SAAVs in the mass spectrometry data. Among the set of 540 SAAVs, 79 are evaluated as deleterious SAAVs based on analysis using the novel AssVar software in which one of the driver mutations found in each protein of KRAS, TP53, and SLC37A4 is further validated using independent selected reaction monitoring (SRM) analysis. Our study represents the most comprehensive discovery of SAAVs to date and the first large-scale detection of deleterious SAAVs in the PANC-1 cell line. This work may serve as the basis for future research in pancreatic cancer and personal immunotherapy and treatment.

Block Design with Common Reference Samples Enables Robust Large-Scale Label-Free Quantitative Proteome Profiling.

Label-free quantitative proteomics has become an increasingly popular tool for profiling global protein abundances. However, one major limitation is the potential performance drift of the LC-MS platform over time, which, in turn, limits its utility for analyzing large-scale sample sets. To address this, we introduce an experimental and data analysis scheme based on a block design with common references within each block for enabling large-scale label-free quantification. In this scheme, a large number of samples (e.g., >100 samples) are analyzed in smaller and more manageable blocks, minimizing instrument drift and variability within individual blocks. Each designated block also contains common reference samples (e.g., controls) for normalization across all blocks. We demonstrated the robustness of this approach by profiling the proteome response of human macrophage THP-1 cells to 11 engineered nanomaterials at two different doses. A total of 116 samples were analyzed in six blocks, yielding an average coverage of 4500 proteins per sample. Following a common reference-based correction, 2537 proteins were quantified with high reproducibility without any imputation of missing values from 116 data sets. The data revealed the consistent quantification of proteins across all six blocks, as illustrated by the highly consistent abundances of house-keeping proteins in all samples and the high levels of correlation among samples from different blocks. The data also demonstrated that label-free quantification is robust and accurate enough to quantify even very subtle abundance changes as well as large fold-changes. Our streamlined workflow is easy to implement and can be readily adapted to other large cohort studies for reproducible label-free proteome quantification.

Accurate Identification of Deamidation and Citrullination from Global Shotgun Proteomics Data Using a Dual-Search Delta Score Strategy.

Proteins with deamidated/citrullinated amino acids play critical roles in the pathogenesis of many human diseases; however, identifying these modifications in complex biological samples has been an ongoing challenge. Herein we present a method to accurately identify these modifications from shotgun proteomics data generated by a deep proteome profiling study of human pancreatic islets obtained by laser capture microdissection. All MS/MS spectra were searched twice using MSGF+ database matching, with and without a dynamic +0.9840 Da mass shift modification on amino acids asparagine, glutamine, and arginine (NQR). Consequently, each spectrum generates two peptide-to-spectrum matches (PSMs) with MSGF+ scores, which were used for the Delta Score calculation. It was observed that all PSMs with positive Delta Score values were clustered with mass errors around 0 ppm, while PSMs with negative Delta Score values were distributed nearly equally within the defined mass error range (20 ppm) for database searching. To estimate false discovery rate (FDR) of modified peptides, a "target-mock" strategy was applied in which data sets were searched against a concatenated database containing "real-modified" (+0.9840 Da) and "mock-modified" (+1.0227 Da) peptide masses. The FDR was controlled to ∼2% using a Delta Score filter value greater than zero. Manual inspection of spectra showed that PSMs with positive Delta Score values contained deamidated/citrullinated fragments in their MS/MS spectra. Many citrullinated sites identified in this study were biochemically confirmed as autoimmunogenic epitopes of autoimmune diseases in literature. The results demonstrated that in situ deamidated/citrullinated peptides can be accurately identified from shotgun tissue proteomics data using this dual-search Delta Score strategy. Raw MS data is available at ProteomeXchange (PXD010150).

Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography-Mass Spectrometry for High-Throughput Single-Cell Proteomics.

Single-cell proteomics can provide critical biological insight into the cellular heterogeneity that is masked by bulk-scale analysis. We have developed a nanoPOTS (nanodroplet processing in one pot for trace samples) platform and demonstrated its broad applicability for single-cell proteomics. However, because of nanoliter-scale sample volumes, the nanoPOTS platform is not compatible with automated LC-MS systems, which significantly limits sample throughput and robustness. To address this challenge, we have developed a nanoPOTS autosampler allowing fully automated sample injection from nanowells to LC-MS systems. We also developed a sample drying, extraction, and loading workflow to enable reproducible and reliable sample injection. The sequential analysis of 20 samples containing 10 ng tryptic peptides demonstrated high reproducibility with correlation coefficients of >0.995 between any two samples. The nanoPOTS autosampler can provide analysis throughput of 9.6, 16, and 24 single cells per day using 120, 60, and 30 min LC gradients, respectively. As a demonstration for single-cell proteomics, the autosampler was first applied to profiling protein expression in single MCF10A cells using a label-free approach. At a throughput of 24 single cells per day, an average of 256 proteins was identified from each cell and the number was increased to 731 when the Match Between Runs algorithm of MaxQuant was used. Using a multiplexed isobaric labeling approach (TMT-11plex), ∼77 single cells could be analyzed per day. We analyzed 152 cells from three acute myeloid leukemia cell lines, resulting in a total of 2558 identified proteins with 1465 proteins quantifiable (70% valid values) across the 152 cells. These data showed quantitative single-cell proteomics can cluster cells to distinct groups and reveal functionally distinct differences.

Fluctuation localization imaging-based fluorescence in situ hybridization (fliFISH) for accurate detection and counting of RNA copies in single cells.

Quantitative gene expression analysis in intact single cells can be achieved using single molecule-based fluorescence in situ hybridization (smFISH). This approach relies on fluorescence intensity to distinguish between true signals, emitted from an RNA copy hybridized with multiple oligonucleotide probes, and background noise. Thus, the precision in smFISH is often compromised by partial or nonspecific probe binding and tissue autofluorescence, especially when only a small number of probes can be fitted to the target transcript. Here we provide an accurate approach for setting quantitative thresholds between true and false signals, which relies on on-off duty cycles of photoswitchable dyes. This fluctuation localization imaging-based FISH (fliFISH) uses on-time fractions (measured over a series of exposures) collected from transcripts bound to as low as 8 probes, which are distinct from on-time fractions collected from nonspecifically bound probes or autofluorescence. Using multicolor fliFISH, we identified radial gene expression patterns in mouse pancreatic islets for insulin, the transcription factor, NKX2-2 and their ratio (Nkx2-2/Ins2). These radial patterns, showing higher values in ß cells at the islet core and lower values in peripheral cells, were lost in diabetic mouse islets. In summary, fliFISH provides an accurate, quantitative approach for detecting and counting true RNA copies and rejecting false signals by their distinct on-time fractions, laying the foundation for reliable single-cell transcriptomics.

Carrier-Assisted Single-Tube Processing Approach for Targeted Proteomics Analysis of Low Numbers of Mammalian Cells.

Heterogeneity in composition is inherent in all cell populations, even those containing a single cell type. Single-cell proteomics characterization of cell heterogeneity is currently achieved by antibody-based technologies, which are limited by the availability of high-quality antibodies. Herein we report a simple, easily implemented, mass spectrometry (MS)-based targeted proteomics approach, termed cLC-SRM (carrier-assisted liquid chromatography coupled to selected reaction monitoring), for reliable multiplexed quantification of proteins in low numbers of mammalian cells. We combine a new single-tube digestion protocol to process low numbers of cells with minimal loss together with sensitive LC-SRM for protein quantification. This single-tube protocol builds upon trifluoroethanol digestion and further minimizes sample losses by tube pretreatment and the addition of carrier proteins. We also optimized the denaturing temperature and trypsin concentration to significantly improve digestion efficiency. cLC-SRM was demonstrated to have sufficient sensitivity for reproducible detection of most epidermal growth factor receptor (EGFR) pathway proteins expressed at levels ≥30 000 and ≥3000 copies per cell for 10 and 100 mammalian cells, respectively. Thus, cLC-SRM enables reliable quantification of low to moderately abundant proteins in less than 100 cells and could be broadly useful for multiplexed quantification of important proteins in small subpopulations of cells or in size-limited clinical samples. Further improvements of this method could eventually enable targeted single-cell proteomics when combined with either SRM or other emerging ultrasensitive MS detection.

Reference genes for accurate normalization of gene expression in wood-decomposing fungi.

Wood-decomposing fungi efficiently decompose plant lignocellulose, and there is increasing interest in characterizing and perhaps harnessing the fungal gene regulation strategies that enable wood decomposition. Proper interpretation of these fungal mechanisms relies on accurate quantification of gene expression, demanding reliable internal control genes (ICGs) as references. Commonly used ICGs such as actin, however, fluctuate among wood-decomposing fungi under defined conditions. In this study, by mining RNA-seq data in silico and validating ICGs in vitro using qRT-PCR, we targeted more reliable ICGs for studying transcriptional responses in wood-decomposing fungi, particularly responses to changing environments (e.g., carbon sources, decomposition stages) in various culture conditions. Using the model brown rot fungus Postia placenta in a first-pass study, our mining efforts yielded 15 constitutively-expressed genes robust in variable carbon sources (e.g., no carbon, glucose, cellobiose, aspen) and cultivation stages (e.g., 15 h, 72 h) in submerged cultures. Of these, we found 7 genes as most suitable ICGs. Expression stabilities of these newly selected ICGs were better than commonly used ICGs, analyzed by NormFinder algorithm and qRT-PCR. In a second-pass, multi-species study in solid wood, our RNA-seq mining efforts revealed hundreds of highly constitutively expressed genes among four wood-decomposing fungi with varying nutritional modes (brown rot, white rot), including a shared core set of ICGs numbering 11 genes. Together, the newly selected ICGs highlighted here will increase reliability when studying gene regulatory mechanisms of wood-decomposing fungi.

Rosette core fungal resistance in Arabidopsis thaliana.

MAIN CONCLUSION: Unlike rosette leaves, the mature Arabidopsis rosette core can display full resistance to Botrytis cinerea revealing the importance for spatial and developmental aspects of plant fungal resistance. Arabidopsis thaliana is a model host to investigate plant defense against fungi. However, many of the reports investigating Arabidopsis fungal defense against the necrotrophic fungus, Botrytis cinerea, utilize rosette leaves as host tissue. Here we report organ-dependent differences in B. cinerea resistance of Arabidopsis. Although wild-type Arabidopsis rosette leaves mount a jasmonate-dependent defense that slows fungal growth, this defense is incapable of resisting fungal devastation. In contrast, as the fungus spreads through infected leaf petioles towards the plant center, or rosette core, there is a jasmonate- and age-dependent fungal penetration blockage into the rosette core. We report evidence for induced and preformed resistance in the rosette core, as direct rosette core inoculation can also result in resistance, but at a lower penetrance relative to infections that approach the core from infected leaf petioles. The Arabidopsis rosette core displays a distinct transcriptome relative to other plant organs, and BLADE ON PETIOLE (BOP) transcripts are abundant in the rosette core. The BOP genes, with known roles in abscission zone formation, are required for full Arabidopsis rosette core B. cinerea resistance, suggesting a possible role for BOP-dependent modifications that may help to restrict fungal susceptibility of the rosette core. Finally, we demonstrate that cabbage and cauliflower, common Brassicaceae crops, also display leaf susceptibility and rosette core resistance to B. cinerea that can involve leaf abscission. Thus, spatial and developmental aspects of plant host resistance play critical roles in resistance to necrotrophic fungal pathogens and are important to our understanding of plant defense mechanisms.

Mass spectrometry-based proteomics for system-level characterization of biological responses to engineered nanomaterials.

The widespread use of engineered nanomaterials or nanotechnology makes the characterization of biological responses to nanomaterials an important area of research. The application of omics approaches, such as mass spectrometry-based proteomics, has revealed new insights into the cellular responses of exposure to nanomaterials, including how nanomaterials interact and alter cellular pathways. In addition, exposure to engineered nanomaterials often leads to the generation of reactive oxygen species and cellular oxidative stress, which implicates a redox-dependent regulation of cellular responses under such conditions. In this review, we discuss quantitative proteomics-based approaches, with an emphasis on redox proteomics, as a tool for system-level characterization of the biological responses induced by engineered nanomaterials. Graphical abstract ᅟ.

All that is silver is not toxic: silver ion and particle kinetics reveals the role of silver ion aging and dosimetry on the toxicity of silver nanoparticles.

BACKGROUND: When suspended in cell culture medium, nano-objects composed of soluble metals such as silver can dissolve resulting in ion formation, altered particle properties (e.g. mass, morphology, etc.), and modulated cellular dose. Cultured cells are exposed not just to nanoparticles but to a complex, dynamic mixture of altered nanoparticles, unbound ions, and ion-ligand complexes. Here, three different cell types (RAW 264.7 macrophages and bone marrow derived macrophages from wild-type C57BL/6 J mice and Scavenger Receptor A deficient (SR-A(-/-)) mice) were exposed to 20 and 110 nm silver nanoparticles, and RAW 264.7 cells were exposed to freshly mixed silver ions, aged silver ions (ions incubated in cell culture medium), and ions formed from nanoparticle dissolution. The In Vitro Sedimentation, Diffusion, Dissolution, and Dosimetry Model (ISD3) was used to predict dose metrics for each exposure scenario. RESULTS: Silver nanoparticles, freshly mixed ions, and ions from nanoparticle dissolution were toxic, while aged ions were not toxic. Macrophages from SR-A(-/-) mice did not take up 20 nm silver nanoparticles as well as wild-types but demonstrated no differences in silver levels after exposure to 110 nm nanoparticles. Dose response modeling with ISD3 predicted dose metrics suggest that amount of ions in cells and area under the curve (AUC) of ion amount in cells are the most predictive of cell viability after nanoparticle and combined nanoparticle/dissolution-formed-ions exposures, respectively. CONCLUSIONS: Results of this study suggest that the unbound silver cation is the ultimate toxicant, and ions formed extracellularly drive toxicity after exposure to nanoparticles. Applying computational modeling (ISD3) to better understand dose metrics for soluble nanoparticles allows for better interpretation of in vitro hazard assessments.

Proteome-wide light/dark modulation of thiol oxidation in cyanobacteria revealed by quantitative site-specific redox proteomics.

Reversible protein thiol oxidation is an essential regulatory mechanism of photosynthesis, metabolism, and gene expression in photosynthetic organisms. Herein, we present proteome-wide quantitative and site-specific profiling of in vivo thiol oxidation modulated by light/dark in the cyanobacterium Synechocystis sp. PCC 6803, an oxygenic photosynthetic prokaryote, using a resin-assisted thiol enrichment approach. Our proteomic approach integrates resin-assisted enrichment with isobaric tandem mass tag labeling to enable site-specific and quantitative measurements of reversibly oxidized thiols. The redox dynamics of ∼2,100 Cys-sites from 1,060 proteins under light, dark, and 3-(3,4-dichlorophenyl)-1,1-dimethylurea (a photosystem II inhibitor) conditions were quantified. In addition to relative quantification, the stoichiometry or percentage of oxidation (reversibly oxidized/total thiols) for ∼1,350 Cys-sites was also quantified. The overall results revealed broad changes in thiol oxidation in many key biological processes, including photosynthetic electron transport, carbon fixation, and glycolysis. Moreover, the redox sensitivity along with the stoichiometric data enabled prediction of potential functional Cys-sites for proteins of interest. The functional significance of redox-sensitive Cys-sites in NADP-dependent glyceraldehyde-3-phosphate dehydrogenase, peroxiredoxin (AhpC/TSA family protein Sll1621), and glucose 6-phosphate dehydrogenase was further confirmed with site-specific mutagenesis and biochemical studies. Together, our findings provide significant insights into the broad redox regulation of photosynthetic organisms.

Sensitive targeted quantification of ERK phosphorylation dynamics and stoichiometry in human cells without affinity enrichment.

Targeted mass spectrometry is a promising technology for site-specific quantification of posttranslational modifications. However, a major constraint is the limited sensitivity for quantifying low-abundance PTMs, requiring the use of affinity reagents for enrichment. Herein, we demonstrate the direct site-specific quantification of ERK phosphorylation isoforms (pT, pY, pTpY) and their relative stoichiometry using a sensitive targeted MS approach termed high-pressure, high-resolution separations with intelligent selection, and multiplexing (PRISM). PRISM provides effective enrichment of target peptides into a given fraction from complex mixture, followed by selected reaction monitoring quantification. Direct quantification of ERK phosphorylation in human mammary epithelial cells (HMEC) was demonstrated from as little as 25 µg tryptic peptides from whole cell lysates. Compared to immobilized metal-ion affinity chromatography, PRISM provided ∼10-fold higher signal intensities, presumably due to the better peptide recovery of PRISM. This approach was applied to quantify ERK phosphorylation dynamics in HMEC treated by different doses of epidermal growth factor at both the peak activation (10 min) and steady state (2 h). The maximal ERK activation was observed with 0.3 and 3 ng/mL doses for 10 min and 2 h time points, respectively. The dose-response profiles of individual phosphorylated isoforms showed that singly phosphorylated pT-ERK never increases significantly, while the increase of pY-ERK paralleled that of pTpY-ERK. This data supports for a processive, rather than distributed model of ERK phosphorylation. The PRISM-SRM quantification of protein phosphorylation illustrates the potential for simultaneous quantification of multiple PTMs.

Signatures of cysteine oxidation on muscle structural and contractile proteins are associated with physical performance and muscle function in older adults: Study of Muscle, Mobility and Aging (SOMMA).

Oxidative stress is considered a contributor to declining muscle function and mobility during aging; however, the underlying molecular mechanisms remain poorly described. We hypothesized that greater levels of cysteine (Cys) oxidation on muscle proteins are associated with decreased measures of mobility. Herein, we applied a novel redox proteomics approach to measure reversible protein Cys oxidation in vastus lateralis muscle biopsies collected from 56 subjects in the Study of Muscle, Mobility and Aging (SOMMA), a community-based cohort study of individuals aged 70 years and older. We tested whether levels of Cys oxidation on key muscle proteins involved in muscle structure and contraction were associated with muscle function (leg power and strength), walking speed, and fitness (VO2 peak on cardiopulmonary exercise testing) using linear regression models adjusted for age, sex, and body weight. Higher oxidation levels of select nebulin Cys sites were associated with lower VO2 peak, while greater oxidation of myomesin-1, myomesin-2, and nebulin Cys sites was associated with slower walking speed. Higher oxidation of Cys sites in key proteins such as myomesin-2, alpha-actinin-2, and skeletal muscle alpha-actin were associated with lower leg power and strength. We also observed an unexpected correlation (R = 0.48) between a higher oxidation level of eight Cys sites in alpha-actinin-3 and stronger leg power. Despite this observation, the results generally support the hypothesis that Cys oxidation of muscle proteins impairs muscle power and strength, walking speed, and cardiopulmonary fitness with aging.

Redox regulation of m6A methyltransferase METTL3 in ß-cells controls the innate immune response in type 1 diabetes.

Type 1 diabetes (T1D) is characterized by the destruction of pancreatic ß-cells. Several observations have renewed the interest in ß-cell RNA sensors and editors. Here, we report that N6-methyladenosine (m6A) is an adaptive ß-cell safeguard mechanism that controls the amplitude and duration of the antiviral innate immune response at T1D onset. m6A writer methyltransferase 3 (METTL3) levels increase drastically in ß-cells at T1D onset but rapidly decline with disease progression. m6A sequencing revealed the m6A hypermethylation of several key innate immune mediators, including OAS1, OAS2, OAS3 and ADAR1 in human islets and EndoC-ßH1 cells at T1D onset. METTL3 silencing enhanced 2'-5'-oligoadenylate synthetase levels by increasing its mRNA stability. Consistently, in vivo gene therapy to prolong Mettl3 overexpression specifically in ß-cells delayed diabetes progression in the non-obese diabetic mouse model of T1D. Mechanistically, the accumulation of reactive oxygen species blocked upregulation of METTL3 in response to cytokines, while physiological levels of nitric oxide enhanced METTL3 levels and activity. Furthermore, we report that the cysteines in position C276 and C326 in the zinc finger domains of the METTL3 protein are sensitive to S-nitrosylation and are important to the METTL3-mediated regulation of oligoadenylate synthase mRNA stability in human ß-cells. Collectively, we report that m6A regulates the innate immune response at the ß-cell level during the onset of T1D in humans.

Redox Regulation of m 6 A Methyltransferase METTL3 in Human ß-cells Controls the Innate Immune Response in Type 1 Diabetes.

Type 1 Diabetes (T1D) is characterized by autoimmune-mediated destruction of insulin-producing ß-cells. Several observations have renewed interest in the innate immune system as an initiator of the disease process against ß-cells. Here, we show that N 6 -Methyladenosine (m 6 A) is an adaptive ß-cell safeguard mechanism that accelerates mRNA decay of the 2'-5'-oligoadenylate synthetase (OAS) genes to control the antiviral innate immune response at T1D onset. m 6 A writer methyltransferase 3 (METTL3) levels increase drastically in human and mouse ß-cells at T1D onset but rapidly decline with disease progression. Treatment of human islets and EndoC-ßH1 cells with pro-inflammatory cytokines interleukin-1 ß and interferon α mimicked the METTL3 upregulation seen at T1D onset. Furthermore, m 6 A-sequencing revealed the m 6 A hypermethylation of several key innate immune mediators including OAS1, OAS2, and OAS3 in human islets and EndoC-ßH1 cells challenged with cytokines. METTL3 silencing in human pseudoislets or EndoC-ßH1 cells enhanced OAS levels by increasing its mRNA stability upon cytokine challenge. Consistently, in vivo gene therapy, to prolong Mettl3 overexpression specifically in ß-cells, delayed diabetes progression in the non-obese diabetic (NOD) mouse model of T1D by limiting the upregulation of Oas pointing to potential therapeutic relevance. Mechanistically, the accumulation of reactive oxygen species blocked METTL3 upregulation in response to cytokines, while physiological levels of nitric oxide promoted its expression in human islets. Furthermore, for the first time to our knowledge, we show that the cysteines in position C276 and C326 in the zinc finger domain of the METTL3 protein are sensitive to S-nitrosylation (SNO) and are significant for the METTL3 mediated regulation of OAS mRNA stability in human ß-cells in response to cytokines. Collectively, we report that m 6 A regulates human and mouse ß-cells to control the innate immune response during the onset of T1D and propose targeting METTL3 to prevent ß-cell death in T1D.