Hepatocyte-intrinsic SMN deficiency drives metabolic dysfunction and liver steatosis in spinal muscular atrophy.

Spinal Muscular Atrophy (SMA) is typically characterized as a motor neuron disease, but extra-neuronal phenotypes are present in almost every organ in severely affected patients and animal models. Extra-neuronal phenotypes were previously underappreciated as patients with severe SMA phenotypes usually died in infancy; however, with current treatments for motor neurons increasing patient lifespan, impaired function of peripheral organs may develop into significant future comorbidities and lead to new treatment-modified phenotypes. Fatty liver is seen in SMA animal models , but generalizability to patients and whether this is due to hepatocyte-intrinsic Survival Motor Neuron (SMN) protein deficiency and/or subsequent to skeletal muscle denervation is unknown. If liver pathology in SMA is SMN-dependent and hepatocyte-intrinsic, this suggests SMN repleting therapies must target extra-neuronal tissues and motor neurons for optimal patient outcome. Here we showed that fatty liver is present in SMA and that SMA patient-specific iHeps were susceptible to steatosis. Using proteomics, functional studies and CRISPR/Cas9 gene editing, we confirmed that fatty liver in SMA is a primary SMN-dependent hepatocyte-intrinsic liver defect associated with mitochondrial and other hepatic metabolism implications. These pathologies require monitoring and indicate need for systematic clinical surveillance and additional and/or combinatorial therapies to ensure continued SMA patient health.

Plasma proteomics of diabetic kidney disease among Asians with younger-onset type 2 diabetes.

CONTEXT: Patients with younger onset of type 2 diabetes (YT2D) have increased risk for kidney failure compared to those with late onset. However, the mechanism of diabetic kidney disease (DKD) progression in this high-risk group is poorly understood. OBJECTIVES: To identify novel biomarkers and potential causal proteins associated with DKD progression in patients with YT2D. DESIGN AND PARTICIPANTS: Among YT2D (T2D onset age ≤ 40 years), 144 DKD progressors (cases) were matched for T2D onset age, sex, and ethnicity with 292 non-progressors (controls) and divided into discovery and validation sets. DKD progression was defined as decline of estimated glomerular filtration rate (eGFR) of 3ml/min/1.73m2 or greater or 40% decline in eGFR from baseline. 1472 plasma proteins were measured through a multiplex immunoassay that uses a proximity extension assay technology. Multivariable logistic regression was used to identify proteins associated with DKD progression. Mendelian randomization (MR) was used to evaluate causal relationship between plasma proteins and DKD progression. RESULTS: 42 plasma proteins were associated with DKD progression, independent of traditional cardio-renal risk factors, baseline eGFR and urine albumin-to-creatinine ratio (uACR). The proteins identified were related to inflammatory and remodelling biological processes. Our findings suggested angiogenin as one of the top signals (odds ratio =5.29, 95% CI 2.39-11.73, P = 4.03 × 10-5). Furthermore, genetically determined plasma angiogenin level was associated with increased odds of DKD progression. CONCLUSION: Large-scale proteomic analysis identified novel proteomic biomarkers for DKD progression in YT2D. Genetic evidence suggest a causal role of plasma angiogenin in DKD progression.

Engineering cell-free systems by chemoproteomic-assisted phenotypic screening.

Phenotypic screening is a valuable tool to both understand and engineer complex biological systems. We demonstrate the functionality of this approach in the development of cell-free protein synthesis (CFPS) technology. Phenotypic screening identified numerous compounds that enhanced protein production in yeast lysate CFPS reactions. Notably, many of these were competitive ATP kinase inhibitors, with the exploitation of their inherent substrate promiscuity redirecting ATP flux towards heterologous protein expression. Chemoproteomic-guided strain engineering partially phenocopied drug effects, with a 30% increase in protein yield observed upon deletion of the ATP-consuming SSA1 component of the HSP70 chaperone. Moreover, drug-mediated metabolic rewiring coupled with template optimization generated the highest protein yields in yeast CFPS to date using a hitherto less efficient, but more cost-effective glucose energy regeneration system. Our approach highlights the utility of target-agnostic phenotypic screening and target identification to deconvolute cell-lysate complexity, adding to the expanding repertoire of strategies for improving CFPS.

Adjunctive pascolizumab in rifampicin-susceptible pulmonary tuberculosis: proof-of-concept, partially-randomised, double-blind, placebo-controlled, dose-escalation trial.

BACKGROUND: Interleukin-4 (IL-4), increased in tuberculosis infection, may impair bacterial killing. Blocking IL-4 confers benefit in animal models. We evaluated safety and efficacy of pascolizumab (humanised anti-IL-4 monoclonal antibody) as adjunctive tuberculosis treatment. METHODS: Participants with rifampicin-susceptible pulmonary tuberculosis received a single intravenous infusion of pascolizumab or placebo; and standard 6-month tuberculosis treatment. Pascolizumab dose increased in successive cohorts: [1] non-randomised 0.05 mg/kg (n = 4); [2] non-randomised 0.5 mg/kg (n = 4); [3] randomised 2.5 mg/kg (n = 9) or placebo (n = 3); [4] randomised 10 mg/kg (n = 9) or placebo (n = 3). Co-primary safety outcome was study-drug-related grade 4 or serious adverse event (G4/SAE); in all cohorts (1-4). Co-primary efficacy outcome was week-8 sputum culture time-to-positivity (TTP); in randomised cohorts (3-4) combined. RESULTS: Pascolizumab levels exceeded IL-4 50% neutralising dose for 8 weeks in 78-100% of participants in cohorts 3-4. There were no study-drug-related G4/SAEs. Median week-8 TTP was 42 days in pascolizumab and placebo groups (p = 0.185). Rate of TTP increase was greater with pascolizumab (difference from placebo 0.011 [95% Bayesian credible interval 0.006 to 0.015] log10TTP/day. CONCLUSIONS: There was no evidence to suggest blocking IL-4 was unsafe. Preliminary efficacy findings are consistent with animal models. This supports further investigation of adjunctive anti-IL-4 interventions for tuberculosis in larger phase 2 trials.

An integrated signature of extracellular matrix proteins and a diastolic function imaging parameter predicts post-MI long-term outcomes.

Background: Patients suffering from acute myocardial infarction (AMI) are at risk of secondary outcomes including major adverse cardiovascular events (MACE) and heart failure (HF). Comprehensive molecular phenotyping and cardiac imaging during the post-discharge time window may provide cues for risk stratification for the outcomes. Materials and methods: In a prospective AMI cohort in New Zealand (N = 464), we measured plasma proteins and lipids 30 days after hospital discharge and inferred a unified partial correlation network with echocardiographic variables and established clinical biomarkers (creatinine, c-reactive protein, cardiac troponin I and natriuretic peptides). Using a network-based data integration approach (iOmicsPASS+), we identified predictive signatures of long-term secondary outcomes based on plasma protein, lipid, imaging markers and clinical biomarkers and assessed the prognostic potential in an independent cohort from Singapore (N = 190). Results: The post-discharge levels of plasma proteins and lipids showed strong correlations within each molecular type, reflecting concerted homeostatic regulation after primary MI events. However, the two molecular types were largely independent with distinct correlation structures with established prognostic imaging parameters and clinical biomarkers. To deal with massively correlated predictive features, we used iOmicsPASS + to identify subnetwork signatures of 211 and 189 data features (nodes) predictive of MACE and HF events, respectively (160 overlapping). The predictive features were primarily imaging parameters, including left ventricular and atrial parameters, tissue Doppler parameters, and proteins involved in extracellular matrix (ECM) organization, cell differentiation, chemotaxis, and inflammation. The network signatures contained plasma protein pairs with area-under-the-curve (AUC) values up to 0.74 for HF prediction in the validation cohort, but the pair of NT-proBNP and fibulin-3 (EFEMP1) was the best predictor (AUC = 0.80). This suggests that there were a handful of plasma proteins with mechanistic and functional roles in predisposing patients to the secondary outcomes, although they may be weaker prognostic markers than natriuretic peptides individually. Among those, the diastolic function parameter (E/e' - an indicator of left ventricular filling pressure) and two ECM proteins, EFEMP1 and follistatin-like 3 (FSTL3) showed comparable performance to NT-proBNP and outperformed left ventricular measures as benchmark prognostic factors for post-MI HF. Conclusion: Post-discharge levels of E/e', EFEMP1 and FSTL3 are promising complementary markers of secondary adverse outcomes in AMI patients.

Oral Peroxisome Proliferator-Activated Receptor-α Agonist Enhances Corneal Nerve Regeneration in Patients With Type 2 Diabetes.

Diabetic corneal neuropathy (DCN) is a common complication of diabetes. However, there are very limited therapeutic options. We investigated the effects of a peroxisome proliferator-activated receptor-α (PPAR-α) agonist, fenofibrate, on 30 patients (60 eyes) with type 2 diabetes. On in vivo confocal microscopy evaluation, there was significant stimulation of corneal nerve regeneration and a reduction in nerve edema after 30 days of oral fenofibrate treatment, as evidenced by significant improvement in corneal nerve fiber density (CNFD) and corneal nerve fiber width, respectively. Corneal epithelial cell morphology also significantly improved in cell circularity. Upon clinical examination, fenofibrate significantly improved patients' neuropathic ocular surface status by increasing tear breakup time along with a reduction of corneal and conjunctival punctate keratopathy. Tear substance P (SP) concentrations significantly increased after treatment, suggesting an amelioration of ocular surface neuroinflammation. The changes in tear SP concentrations was also significantly associated with improvement in CNFD. Quantitative proteomic analysis demonstrated that fenofibrate significantly upregulated and modulated the neurotrophin signaling pathway and linolenic acid, cholesterol, and fat metabolism. Complement cascades, neutrophil reactions, and platelet activation were also significantly suppressed. Our results showed that fenofibrate could potentially be a novel treatment for patients with DCN.

Variability of the Plasma Lipidome and Subclinical Coronary Atherosclerosis.

OBJECTIVE: While the risk of acute coronary events has been associated with biological variability of circulating cholesterol, the association with variability of other atherogenic lipids remains less understood. We evaluated the longitudinal variability of 284 lipids and investigated their association with asymptomatic coronary atherosclerosis. Approach and Results: Circulating lipids were extracted from fasting blood samples of 83 community-sampled symptom-free participants (age 41-75 years), collected longitudinally over 6 months. Three types of coronary plaque volume (calcified, lipid-rich, and fibrotic) were quantified using computed tomography coronary angiogram. We first deconvoluted between-subject (CVg) and within-subject (CVw) lipid variabilities. We then tested whether the mean lipid abundance was different across groups categorized by Framingham risk score and plaques phenotypes (lipid-rich, fibrotic, and calcified). Finally, we investigated whether visit-to-visit variability of each lipid was associated with plaque burden. Most lipids (72.5%) exhibited higher CVg than CVw. Among the lipids (n=145) with 1.2-fold higher CVg than CVw, 26 species including glycerides and ceramides were significantly associated with Framingham risk score and the 3 plaque phenotypes (false discovery rate <0.05). In an exploratory analysis of person-specific visit-to-visit variability without multiple testing correction, high variability of 3 lysophospholipids (lysophosphatidylethanolamines 16:0, 18:0, and lysophosphatidylcholine O-18:1) was associated with lipid-rich and fibrotic (noncalcified) plaque volume while high variability of diacylglycerol 18:1_20:0, triacylglycerols 52:2, 52:3, and 52:4, ceramide d18:0/20:0, dihexosylceramide d18:1/16:0, and sphingomyelin 36:3 was associated with calcified plaque volume. CONCLUSIONS: High person-specific longitudinal variation of specific nonsterol lipids is associated with the burden of subclinical coronary atherosclerosis. Larger studies are needed to confirm these exploratory findings.

Plasma Metabolome and Lipidome Associations with Type 2 Diabetes and Diabetic Nephropathy.

We conducted untargeted metabolomics analysis of plasma samples from a cross-sectional case-control study with 30 healthy controls, 30 patients with diabetes mellitus and normal renal function (DM-N), and 30 early diabetic nephropathy (DKD) patients using liquid chromatography-mass spectrometry (LC-MS). We employed two different modes of MS acquisition on a high-resolution MS instrument for identification and semi-quantification, and analyzed data using an advanced multivariate method for prioritizing differentially abundant metabolites. We obtained semi-quantification data for 1088 unique compounds (~55% lipids), excluding compounds that may be either exogenous compounds or treated as medication. Supervised classification analysis over a confounding-free partial correlation network shows that prostaglandins, phospholipids, nucleotides, sugars, and glycans are elevated in the DM-N and DKD patients, whereas glutamine, phenylacetylglutamine, 3-indoxyl sulfate, acetylphenylalanine, xanthine, dimethyluric acid, and asymmetric dimethylarginine are increased in DKD compared to DM-N. The data recapitulate the well-established plasma metabolome changes associated with DM-N and suggest uremic solutes and oxidative stress markers as the compounds indicating early renal function decline in DM patients.

Polyubiquitin Chains Linked by Lysine Residue 48 (K48) Selectively Target Oxidized Proteins In Vivo.

Aims: Ubiquitin is a highly conserved protein modifier that heavily accumulates during the oxidative stress response. Here, we investigated the role of the ubiquitination system, particularly at the linkage level, in the degradation of oxidized proteins. The function of ubiquitin in the removal of oxidized proteins remains elusive because of the wide range of potential targets and different roles that polyubiquitin chains play. Therefore, we describe in detail the dynamics of the K48 ubiquitin response as the canonical signal for protein degradation. We identified ubiquitin targets and defined the relationship between protein ubiquitination and oxidation during the stress response. Results: Combining oxidized protein isolation, linkage-specific ubiquitination screens, and quantitative proteomics, we found that K48 ubiquitin accumulated at both the early and late phases of the stress response. We further showed that a fraction of oxidized proteins are conjugated with K48 ubiquitin. We identified ∼750 ubiquitinated proteins and ∼400 oxidized proteins that were modified during oxidative stress, and around half of which contain both modifications. These proteins were highly abundant and function in translation and energy metabolism. Innovation and Conclusion: Our work showed for the first time that K48 ubiquitin modifies a large fraction of oxidized proteins, demonstrating that oxidized proteins can be targeted by the ubiquitin/proteasome system. We suggest that oxidized proteins that rapidly accumulate during stress are subsequently ubiquitinated and degraded during the late phase of the response. This delay between oxidation and ubiquitination may be necessary for reprogramming protein dynamics, restoring proteostasis, and resuming cell growth.

iOmicsPASS: network-based integration of multiomics data for predictive subnetwork discovery.

Computational tools for multiomics data integration have usually been designed for unsupervised detection of multiomics features explaining large phenotypic variations. To achieve this, some approaches extract latent signals in heterogeneous data sets from a joint statistical error model, while others use biological networks to propagate differential expression signals and find consensus signatures. However, few approaches directly consider molecular interaction as a data feature, the essential linker between different omics data sets. The increasing availability of genome-scale interactome data connecting different molecular levels motivates a new class of methods to extract interactive signals from multiomics data. Here we developed iOmicsPASS, a tool to search for predictive subnetworks consisting of molecular interactions within and between related omics data types in a supervised analysis setting. Based on user-provided network data and relevant omics data sets, iOmicsPASS computes a score for each molecular interaction, and applies a modified nearest shrunken centroid algorithm to the scores to select densely connected subnetworks that can accurately predict each phenotypic group. iOmicsPASS detects a sparse set of predictive molecular interactions without loss of prediction accuracy compared to alternative methods, and the selected network signature immediately provides mechanistic interpretation of the multiomics profile representing each sample group. Extensive simulation studies demonstrate clear benefit of interaction-level modeling. iOmicsPASS analysis of TCGA/CPTAC breast cancer data also highlights new transcriptional regulatory network underlying the basal-like subtype as positive protein markers, a result not seen through analysis of individual omics data.

Exploiting Interdata Relationships in Next-generation Proteomics Analysis.

Mass spectrometry based proteomics and other technologies have matured to enable routine quantitative, system-wide analysis of concentrations, modifications, and interactions of proteins, mRNAs, and other molecules. These studies have allowed us to move toward a new field concerned with mining information from the combination of these orthogonal data sets, perhaps called "integromics." We highlight examples of recent studies and tools that aim at relating proteomic information to mRNAs, genetic associations, and changes in small molecules and lipids. We argue that productive data integration differs from parallel acquisition and interpretation and should move toward quantitative modeling of the relationships between the data. These relationships might be expressed by temporal information retrieved from time series experiments, rate equations to model synthesis and degradation, or networks of causal, evolutionary, physical, and other interactions. We outline steps and considerations toward such integromic studies to exploit the synergy between data sets.

Plasma Protein and MicroRNA Biomarkers of Insulin Resistance: A Network-Based Integrative -Omics Analysis.

Although insulin resistance (IR) is a key pathophysiologic condition underlying various metabolic disorders, impaired cellular glucose uptake is one of many manifestations of metabolic derangements in the human body. To study the systems-wide molecular changes associated with obesity-dependent IR, we integrated information on plasma proteins and microRNAs in eight obese insulin-resistant (OIR, HOMA-IR > 2.5) and nine lean insulin-sensitive (LIS, HOMA-IR < 1.0) normoglycemic males. Of 374 circulating miRNAs we profiled, 65 species increased and 73 species decreased in the OIR compared to the LIS subjects, suggesting that the overall balance of the miRNA secretome is shifted in the OIR subjects. We also observed that 40 plasma proteins increased and 4 plasma proteins decreased in the OIR subjects compared to the LIS subjects, and most proteins are involved in metabolic and endocytic functions. We used an integrative -omics analysis framework called iOmicsPASS to link differentially regulated miRNAs with their target genes on the TargetScan map and the human protein interactome. Combined with tissue of origin information, the integrative analysis allowed us to nominate obesity-dependent and obesity-independent protein markers, along with potential sites of post-transcriptional regulation by some of the miRNAs. We also observed the changes in each -omics platform that are not linked by the TargetScan map, suggesting that proteins and microRNAs provide orthogonal information for the progression of OIR. In summary, our integrative analysis provides a network of elevated plasma markers of OIR and a global shift of microRNA secretome composition in the blood plasma.

EBprotV2: A Perseus Plugin for Differential Protein Abundance Analysis of Labeling-Based Quantitative Proteomics Data.

We present EBprotV2, a Perseus plugin for peptide-ratio-based differential protein abundance analysis in labeling-based proteomics experiments. The original version of EBprot models the distribution of log-transformed peptide-level ratios as a Gaussian mixture of differentially abundant proteins and nondifferentially abundant proteins and computes the probability score of differential abundance for each protein based on the reproducible magnitude of peptide ratios. However, the fully parametric model can be inflexible, and its R implementation is time-consuming for data sets containing a large number of peptides (e.g., >100 000). The new tool built in the C++ language is not only faster in computation time but also equipped with a flexible semiparametric model that handles skewed ratio distributions better. We have also developed a Perseus plugin for EBprotV2 for easy access to the tool. In addition, the tool now offers a new submodule (MakeGrpData) to transform label-free peptide intensity data into peptide ratio data for group comparisons and performs differential abundance analysis using mixture modeling. This approach is especially useful when the label-free data have many missing peptide intensity data points.

Metabolic Remodeling during Liver Regeneration.

Liver disease is linked to a decreased capacity of hepatocytes to divide. In addition, cellular metabolism is important for tissue homeostasis and regeneration. Since metabolic changes are a hallmark of liver disease, we investigated the connections between metabolism and cell division. We determined global metabolic changes at different stages of liver regeneration using a combination of integrated transcriptomic and metabolomic analyses with advanced functional redox in vivo imaging. Our data indicate that blocking hepatocyte division during regeneration leads to mitochondrial dysfunction and downregulation of oxidative pathways. This resulted in an increased redox ratio and hyperactivity of alanine transaminase allowing the production of alanine and α-ketoglutarate from pyruvate when mitochondrial functions are impaired. Our data suggests that during liver regeneration, cell division leads to hepatic metabolic remodeling. Moreover, we demonstrate that hepatocytes are equipped with a flexible metabolic machinery able to adapt dynamically to changes during tissue regeneration.

Ikk2 regulates cytokinesis during vertebrate development.

NFκB signaling has a pivotal role in regulation of development, innate immunity, and inflammation. Ikk2 is one of the two critical kinases that regulate the NFκB signaling pathway. While the role of Ikk2 in immunity, inflammation and oncogenesis has received attention, an understanding of the role of Ikk2 in vertebrate development has been compounded by the embryonic lethality seen in mice lacking Ikk2. We find that despite abnormal angiogenesis in IKK2 zygotic mutants of zebrafish, the maternal activity of Ikk2 supports embryogenesis and maturation of fertile animals and allows to study the role of IKK2 in development. Maternal-zygotic ikk2 mutants represent the first vertebrates globally devoid of maternal and zygotic Ikk2 activity. They are defective in cell proliferation as evidenced by abnormal cytokinesis, nuclear enlargement and syncytialisation of a significant portion of blastoderm. We further document that reduced phosphorylation of Aurora A by Ikk2 could underlie the basis of these defects in cell division.

Red Meat Intake and Risk of ESRD.

Randomized controlled trials suggest that protein restriction may retard the progression of CKD toward ESRD. However, the effects of dietary protein intake level and the food sources of dietary protein on the risk of ESRD in the general population remain unclear. We investigated these effects in the Singapore Chinese Health Study, a prospective population-based cohort that recruited 63,257 Chinese adults aged 45-74 years from 1993 to 1998. We collected habitual diet information via a validated semiquantitative food frequency questionnaire and identified ESRD via record linkage with a nationwide registry. In all, 951 cases of ESRD occurred over a mean follow-up of 15.5 years. Regarding total protein intake, compared with the lowest quartile, the three higher quartiles combined had a hazard ratio for ESRD of 1.24 (95% confidence interval [95% CI], 1.05 to 1.46), but the dose-dependent association across the quartiles was not statistically significant (Ptrend=0.16). Red meat intake strongly associated with ESRD risk in a dose-dependent manner (hazard ratio for highest quartile versus lowest quartile,1.40 [95% CI, 1.15 to 1.71; Ptrend<0.001]). Intake of poultry, fish, eggs, or dairy products did not associate with risk of ESRD. In substitution analysis, replacing one serving of red meat with other food sources of protein associated with a maximum relative risk reduction of 62.4% (95% CI, 33.1 to 78.9; P<0.01). Our study shows that red meat intake may increase the risk of ESRD in the general population and substituting alternative sources of protein may reduce the incidence of ESRD.

Development of a Semi-Quantitative Food Frequency Questionnaire to Assess the Dietary Intake of a Multi-Ethnic Urban Asian Population.

Assessing habitual food consumption is challenging in multi-ethnic cosmopolitan settings. We systematically developed a semi-quantitative food frequency questionnaire (FFQ) in a multi-ethnic population in Singapore, using data from two 24-h dietary recalls from a nationally representative sample of 805 Singapore residents of Chinese, Malay and Indian ethnicity aged 18-79 years. Key steps included combining reported items on 24-h recalls into standardized food groups, developing a food list for the FFQ, pilot testing of different question formats, and cognitive interviews. Percentage contribution analysis and stepwise regression analysis were used to identify foods contributing cumulatively ≥90% to intakes and individually ≥1% to intake variance of key nutrients, for the total study population and for each ethnic group separately. Differences between ethnic groups were observed in proportions of consumers of certain foods (e.g., lentil stews, 1%-47%; and pork dishes, 0%-50%). The number of foods needed to explain variability in nutrient intakes differed substantially by ethnic groups and was substantially larger for the total population than for separate ethnic groups. A 163-item FFQ covered >95% of total population intake for all key nutrients. The methodological insights provided in this paper may be useful in developing similar FFQs in other multi-ethnic settings.

Plasma fatty acids, oxylipins, and risk of myocardial infarction: the Singapore Chinese Health Study.

We aimed to examine the prospective association between plasma FAs, oxylipins, and risk of acute myocardial infarction (AMI) in a Singapore Chinese population. A nested case-control study with 744 incident AMI cases and 744 matched controls aged 47-83 years was conducted within the Singapore Chinese Health Study. Nineteen plasma FAs and 12 oxylipins were quantified using MS. These were grouped into 12 FA clusters and 5 oxylipin clusters using hierarchical clustering, and their associations with AMI risk were assessed. Long-chain n-3 FAs [odds ratio (OR) = 0.67 per SD increase, 95% confidence interval (CI): 0.53-0.84, P < 0.001] and stearic acid (OR = 0.65, 95% CI: 0.44-0.97, P = 0.03) were inversely associated with AMI risk, whereas arachidonic acid (AA) was positively associated with AMI risk (OR = 1.25, 95% CI: 1.03-1.52, P = 0.02) in the multivariable model with adjustment for other FAs. Further adjustment for oxylipins did not substantially change these associations. An inverse association was observed between AA-derived oxylipin, thromboxane (TX)B2, and AMI risk (OR = 0.81, 95% CI: 0.71-0.93, P = 0.003). Circulating long-chain n-3 FAs and stearic acid were associated with a lower and AA was associated with a higher AMI risk in this Chinese population. The association between the oxylipin TXB2 and AMI requires further research.

SAINTq: Scoring protein-protein interactions in affinity purification - mass spectrometry experiments with fragment or peptide intensity data.

SAINT (Significance Analysis of INTeractome) is a probabilistic method for scoring bait-prey interactions against negative controls in affinity purification - mass spectrometry (AP-MS) experiments. Our published SAINT algorithms use spectral counts or protein intensities as the input for calculating the probability of true interaction, which enables objective selection of high-confidence interactions with false discovery control. With the advent of new protein quantification methods such as Data Independent Acquisition (DIA), we redeveloped the scoring method to utilize the reproducibility information embedded in the peptide or fragment intensity data as a key scoring criterion, bypassing protein intensity summarization required in the previous SAINT workflow. The new software package, SAINTq, addresses key issues in the interaction scoring based on intensity data, including treatment of missing values and selection of peptides and fragments for scoring each prey protein. We applied SAINTq to two independent DIA AP-MS data sets profiling the interactome of MEPCE and EIF4A2 and that of 14-3-3ß, and benchmarked the performance in terms of recovering previously reported literature interactions in the iRefIndex database. In both data sets, the SAINTq analysis using the fragment-level intensity data led to the most sensitive detection of literature interactions at the same level of specificity. This analysis outperforms the analysis using protein intensity data summed from fragment intensity data that is equivalent to the model in SAINTexpress.

Differential dynamics of the mammalian mRNA and protein expression response to misfolding stress.

The relative importance of regulation at the mRNA versus protein level is subject to ongoing debate. To address this question in a dynamic system, we mapped proteomic and transcriptomic changes in mammalian cells responding to stress induced by dithiothreitol over 30 h. Specifically, we estimated the kinetic parameters for the synthesis and degradation of RNA and proteins, and deconvoluted the response patterns into common and unique to each regulatory level using a new statistical tool. Overall, the two regulatory levels were equally important, but differed in their impact on molecule concentrations. Both mRNA and protein changes peaked between two and eight hours, but mRNA expression fold changes were much smaller than those of the proteins. mRNA concentrations shifted in a transient, pulse-like pattern and returned to values close to pre-treatment levels by the end of the experiment. In contrast, protein concentrations switched only once and established a new steady state, consistent with the dominant role of protein regulation during misfolding stress. Finally, we generated hypotheses on specific regulatory modes for some genes.