MS1-based label-free proteomics using a quadrupole orbitrap mass spectrometer

A dataset for developing proteomic tools for pathogen detection via differential cell lysis of whole blood samples

This data descriptor presents a curated dataset for pathogen detection and identification (Staphylococcus aureus, Pseudomonas aeruginosa, and Candida albicans) directly from whole-blood samples. The dataset was created using differential cell lysis combined with rapid extraction, digestion, and mass spectrometry-based proteomics. Our method offers a rapid diagnostic alternative to traditional culture, enabling timely disease management, such as sepsis. Highlighting our dataset's uniqueness, it features a three-tier structure: Spectral Libraries of Pathogens for identifying peptide peaks for putative biomarkers; Spiked pathogen in blood MS data for biomarker panel optimization through varied concentration samples; and Parallel Reaction Monitoring (PRM) data from sepsis patients for validating our biomarker panel, achieving 83.3% sensitivity within seven hours without microbial enrichment culture. This dataset serves as a comprehensive reference for bioinformatic tool development and biomarker panel proposals, advancing microbial detection, antimicrobial resistance, and epidemiological studies.

Cabozantinib inhibits the growth of lenvatinib-resistant hepatoma cells restoring FTCD expression

Cabozantinib is a newly developed tyrosine kinase inhibitor, which is applied on patients with hepatocellular carcinoma (HCC) unresponsive to conventional tyrosine kinase inhibitors, including lenvatinib. However, the mechanism of cabozantinib efficacy for lenvatinib-resistant tumor cells has not been well established in basic studies. The purpose of this study is to elucidate the mechanisms by which cabozantinib inhibits tumor growth of lenvatinib-resistant hepatocellular carcinoma cell lines in vitro and in vivo. We established a lenvatinib-resistant Hep3B cell line (Hep3B-LR) and evaluated the inhibitory effect of cabozantinib on the growth of Hep3B-LR cells. Hep3B-LR exhibited approximately 20 times greater IC50 for lenvatinib than the wild type. Compared with wild-type Hep3B, Hep3B-LR was characterized by enhanced expression of EGFR, MET and ErbB2. Cabozantinib suppressed tumor growth of Hep3B-LR in vitro and in vivo. Microarray analysis and real-time qPCR using the xenografts revealed cabozantinib downregulated miR-126-3p, a tumor suppressor miRNA, suggesting that miR-126-3p did not contribute to tumor inhibitory effect of cabozantinib. Proteome analysis using xenograft tissues demonstrated an upregulation of FTCD, a tumor suppressor gene, by cabozantinib administration. The enhanced expression of FTCD by cabozantinib was confirmed by western blot and immunohistochemistry analysis. Furthermore, FTCD expression in Hep3B-LR before cabozantinib administration was weaker than that in wild-type Hep3B. FTCD expression was weakened along with acquisition of lenvatinib-resistance, and was restored by cabozantinib administration. FTCD may be a novel therapeutic target of cabozantinib in case of lenvatinib treatment failure.

Proteomics of human platelet lysates and insight from animal studies on platelet protein diffusion to hippocampus upon intranasal administration

Human platelet lysates (HPLs) from allogeneic platelet concentrates (PCs) are biomaterials, which are rich in various trophic factors, increasingly used in regenerative medicine and biotherapy. Understanding how preparation methods influence the HPL protein profile, biological function, and clinical outcomes is crucial. Our study sheds light on the proteomes and functionality of different HPLs, with the aim of advancing their scientifically grounded clinical applications. To achieve this, PCs suspended in plasma underwent three distinct processing methods, resulting in seven HPL types. We used three characterization techniques: label-free proteomics and tandem mass tag (TMT)-based quantitative proteomics, both before and after the immunodepletion of abundant plasma proteins. Bioinformatic tools assessed the proteome, and western blotting validated our quantitative proteomics data. Subsequent pre-clinical studies with fluorescent labeling and label-free proteomics were used as a proof of concept for brain diffusion. Our findings revealed 1441 proteins detected using the label-free method, 952 proteins from the TMT experiment before and after depletion, and 1114 proteins from the subsequent TMT experiment on depleted HPLs. Most detected proteins were cytoplasmic, playing key roles in catalysis, hemostasis, and immune responses. Notably, the processing methodologies significantly influenced HPL compositions, their canonical pathways, and, consequently, their functionality. Each HPL exhibited specific abundant proteins, providing valuable insight for tailored clinical applications. Immunoblotting results for selected proteins corroborated our quantitative proteomics data. The diffusion and differential effects to the hippocampus of a neuroprotective HPL administered intranasally to mice were demonstrated. This proteomics study advances our understanding of HPLs, suggesting ways to standardize and customize their production for better clinical efficacy in regenerative medicine and biotherapy. Proteomic analyses also offered objective evidence that HPPL, upon intranasal delivery, not only effectively diffuses to the hippocampus but also alters protein expression in mice, bolstering its potential as a treatment for memory impairments.

Degradation of p0071 and p120-catenin during adherens junction disassembly by Leptospira interrogans

Leptospira interrogans disseminates hematogenously to reach the target organs by disrupting epithelial adherens junctions (AJs), thus causing leptospirosis, which is a globally neglected zoonotic disease. L. interrogans induces E-cadherin (E-cad) endocytosis and cytoskeletal rearrangement during AJ disassembly, but the detailed mechanism remains unknown. Elucidation of AJ disassembly mechanisms will guide new approaches to developing vaccines and diagnostic methods. In this study, we combine proteomic and imaging analysis with chemical inhibition studies to demonstrate that disrupting the AJs of renal proximal tubule epithelial cells involves the degradation of two armadillo repeat-containing proteins, p0071 and p120-catenin, that stabilize E-cad at the plasma membrane. Combining proteasomal and lysosomal inhibitors substantially prevented p120-catenin degradation, and monolayer integrity destruction without preventing p0071 proteolysis. In contrast, the pan-caspase inhibitor Z-VAD-FMK inhibited p0071 proteolysis and displacement of both armadillo repeat-containing proteins from the cell-cell junctions. Our results show that L. interrogans induces p120-catenin and p0071 degradation, which mutually regulates E-cad stability by co-opting multiple cellular degradation pathways. This strategy may allow L. interrogans to disassemble AJs and disseminate through the body efficiently.

IQMMA: Efficient MS1 Intensity Extraction Pipeline Using Multiple Feature Detection Algorithms for DDA Proteomics

One of the key steps in data dependent acquisition (DDA) proteomics is detection of peptide isotopic clusters, also called "features", in MS1 spectra and matching them to MS/MS-based peptide identifications. A number of peptide feature detection tools became available in recent years, each relying on its own matching algorithm. Here, we provide an integrated solution, the intensity-based Quantitative Mix and Match Approach (IQMMA), which integrates a number of untargeted peptide feature detection algorithms and returns the most probable intensity values for the MS/MS-based identifications. IQMMA was tested using available proteomic data acquired for both well-characterized (ground truth) and real-world biological samples, including a mix of Yeast and E. coli digests spiked at different concentrations into the Human K562 digest used as a background, and a set of glioblastoma cell lines. Three open-source feature detection algorithms were integrated: Dinosaur, biosaur2, and OpenMS FeatureFinder. None of them was found optimal when applied individually to all the data sets employed in this work; however, their combined use in IQMMA improved efficiency of subsequent protein quantitation. The software implementing IQMMA is freely available at https://github.com/PostoenkoVI/IQMMA under Apache 2.0 license.

Redifferentiated cardiomyocytes retain residual dedifferentiation signatures and are protected against ischemic injury

Cardiomyocyte proliferation and dedifferentiation have fueled the field of regenerative cardiology in recent years, whereas the reverse process of redifferentiation remains largely unexplored. Redifferentiation is characterized by the restoration of function lost during dedifferentiation. Previously, we showed that ERBB2-mediated heart regeneration has these two distinct phases: transient dedifferentiation and redifferentiation. Here we survey the temporal transcriptomic and proteomic landscape of dedifferentiation-redifferentiation in adult mouse hearts and reveal that well-characterized dedifferentiation features largely return to normal, although elements of residual dedifferentiation remain, even after the contractile function is restored. These hearts appear rejuvenated and show robust resistance to ischemic injury, even 5 months after redifferentiation initiation. Cardiomyocyte redifferentiation is driven by negative feedback signaling and requires LATS1/2 Hippo pathway activity. Our data reveal the importance of cardiomyocyte redifferentiation in functional restoration during regeneration but also protection against future insult, in what could lead to a potential prophylactic treatment against ischemic heart disease for at-risk patients.

Heat shock protein 27 regulates myogenic and self-renewal potential of bovine satellite cells under heat stress

While satellite cells play a key role in the hypertrophy, repair, and regeneration of skeletal muscles, their response to heat exposure remains poorly understood, particularly in beef cattle. This study aimed to investigate the changes in the transcriptome, proteome, and proliferation capability of bovine satellite cells in response to different levels of heat stress (HS) and exposure times. Satellite cells were isolated from 3-mo-old Holstein bulls (body weight: 77.10 ± 2.02 kg) and subjected to incubation under various temperature conditions: 1) control (38 °C; CON), 2) moderate (39.5 °C; MHS), and extreme (41 °C; EHS) for different durations ranging from 0 to 48 h. Following 3 h of exposure to extreme heat (EHS), satellite cells exhibited significantly increased gene expression and protein abundance of heat shock proteins (HSPs; HSP70, HSP90, HSP20) and paired box gene 7 (Pax7; P < 0.05). HSP27 expression peaked at 3 h of EHS and remained elevated until 24 h of exposure (P < 0.05). In contrast, the expression of myogenic factor 5 (Myf5) and paired box gene 3 (Pax3) was decreased by EHS compared to the control at 3 h of exposure (P < 0.05). Notably, the introduction of HSP27 small interference RNA (siRNA) transfection restored Myf5 expression to control levels, suggesting an association between HSP27 and Myf5 in regulating the self-renewal properties of satellite cells upon heat exposure. Immunoprecipitation experiments further confirmed the direct binding of HSP27 to Myf5, supporting its role as a molecular chaperone for Myf5. Protein-protein docking algorithms predicted a high probability of HSP27-Myf5 interaction as well. These findings indicate that extreme heat exposure intrinsically promotes the accumulation of HSPs and modulates the early myogenic regulatory factors in satellite cells. Moreover, HSP27 acts as a molecular chaperone by binding to Myf5, thereby regulating the division or differentiation of satellite cells in response to HS. The results of this study provide a better understanding of muscle physiology in heat-stressed cells, while unraveling the intricate molecular mechanisms that underlie the HS response in satellite cells.

Proteomic analysis of adipose tissue revealing differentially abundant proteins in highly efficient mid-lactating dairy cows

The improvement of nutrient utilization efficiency in dairy cows represents an important task in view of the current rising demand for animal products and sustainable resource usage. In this perspective, the identification of appropriate markers to identify the most efficient animals for dairy production becomes a crucial factor. Residual feed intake (RFI), which represents the difference between predicted and actual intake, is used to define the efficiency of cows. In this study, subcutaneous adipose tissue (AT) was collected from five high efficient (HEF) and five low efficient (LEF) mid-lactation Holstein dairy cows, that represented subgroups of the 20% lowest RFI values (HEF) and highest 20% RFI values (LEF), out of a cohort of 155 cows that were examined for feed efficiency at the individual dairy barn at Volcani Institute, Israel. Adipose samples were examined for proteomic analysis by nano-LC/MS–MS and gene expression by RT-PCR. A total of 101 differential proteins (P ≤ 0.05 and fold change ± 1.5) and two protein networks related to feed efficiency were found between HEF and LEF cows. Among the enriched top canonical pathways, FAT10 signaling, EIF2 signaling, Sirtuin signaling, Acute phase response signaling, Protein ubiquitination and mTOR signaling pathways were related to feed efficiency in AT. Furthermore, abundance of transferrin (TF; FC = 78.35, P = 0.02) enriched pathways, including mTOR signaling, LXR/RXR and FXR/RXR activation was found in AT of HEF cows. Relative mRNA expression of RBM39, which is involved in energy metabolism, was decreased in AT of HEF versus LEF. The relationship found between the AT proteins and/or metabolic pathways and the feed efficiency demonstrates that AT may reflect metabolic adaptations to high efficiency, and suggests that these proteins together with their metabolic mechanisms are suitable candidates as biomarkers to identify efficient cows for dairy production.

Proteomic analysis of heat-stable proteins revealed an increased proportion of proteins with compositionally biased regions

Intrinsically disordered proteins (IDPs) have been in the spotlight for their unique properties, such as their lack of secondary structures and low sequence complexity. Alpha-synuclein and tau are representative disease-related IDPs with low complexity regions in their sequences, accumulating in the brains of patients with Parkinson disease and Alzheimer disease, respectively. Their heat resistance in particular was what attracted our attention. We assumed that there exist many other unidentified proteins that are resistant to heat-treatment, referred to as heat-stable proteins, which would also have low sequence complexity. In this study, we performed proteomic analysis of heat-stable proteins of mouse brains and found that proteins with compositionally biased regions are abundant in the heat-stable proteins. The proteins related to neurodegeneration are known to undergo different types of post-translational modifications (PTMs) such as phosphorylation and ubiquitination. We then investigated the heat-stability and aggregation properties of phosphorylated synuclein and tau with different phosphorylation sites. We suggest that PTMs can be important factors that determine the heat-stability and aggregation properties of a protein. IDPs identified in the heat-stable proteins of mouse brains would be candidates for the pathogenic proteins for neurodegeneration.

Hornerin deposits in neuronal intranuclear inclusion disease: direct identification of proteins with compositionally biased regions in inclusions

Neuronal intranuclear inclusion disease (NIID) is a neurodegenerative disorder, characterized by the presence of eosinophilic inclusions (NIIs) within nuclei of central and peripheral nervous system cells. This study aims to identify the components of NIIs, which have been difficult to analyze directly due to their insolubility. In order to establish a method to directly identify the components of NIIs, we first analyzed the huntingtin inclusion-rich fraction obtained from the brains of Huntington disease model mice. Although the sequence with expanded polyglutamine could not be identified by liquid-chromatography mass spectrometry, amino acid analysis revealed that glutamine of the huntingtin inclusion-rich fraction increased significantly. This is compatible with the calculated amino acid content of the transgene product. Therefore, we applied this method to analyze the NIIs of diseased human brains, which may have proteins with compositionally biased regions, and identified a serine-rich protein called hornerin. Since the analyzed NII-rich fraction was also serine-rich, we suggested hornerin as a major component of the NIIs. A specific distribution of hornerin in NIID was also investigated by Matrix-assisted laser desorption/ionization imaging mass spectrometry and immunofluorescence. Finally, we confirmed a variant of hornerin by whole-exome sequencing and DNA sequencing. This study suggests that hornerin may be related to the pathological process of this NIID, and the direct analysis of NIIs, especially by amino acid analysis using the NII-rich fractions, would contribute to a deeper understanding of the disease pathogenesis.

StatsPro: Systematic integration and evaluation of statistical approaches for detecting differential expression in label-free quantitative proteomics

Quantitative label-free mass spectrometry (MS) is an increasingly powerful technology for profiling thousands of proteins from complex biological samples. One of the primary goals of analyses performed on such proteomics data is to detect differentially expressed proteins (DEPs) under different experimental conditions. Many statistical methods have been developed and assessed for DEP detection in various proteomics studies. However, it remains a challenge for many proteomics scientists to choose an appropriate statistical procedure. Therefore, in this study, we organized 12 common testing algorithms and 6 P-value combination methods and further provided Cohen's d effect size for every protein and three evaluation criteria to help proteomics scientists investigate their influence on DEP detection in a systematic manner. To promote the widespread use of these methods, we developed a user-friendly web tool, StatsPro, and presented two case studies involving label-free quantitative proteomics data obtained using data-dependent acquisition and data-independent acquisition to illustrate its practicability. This tool is freely available in our GitHub repository (https://github.com/YanglabWCH/StatsPro/). SIGNIFICANCE: One of the primary goals of analyses performed on liquid chromatography-mass spectrometry (LC-MS) based proteomics data is to detect differentially expressed proteins (DEPs) under different experimental conditions. Despite of many research efforts have been proposed to detect DEPs, to date, there is a scarcity of efficient, systematic, and easy-to-handle tools that are tailored for proteomics scientists to choose an appropriate statistical procedure. Herein, we present a new tool, StatsPro, to enable implementation and evaluation of different statistical methods for proteomics scientists. This tool has two significant advances compared to existing software: a) It integrates up to 18 common statistical approaches (12 statistical tests and 6 P-value combination strategies) and performs Cohen's d effect size systematically for users, moreover, it provides a web-based interface and can be quite conveniently operated by users, even those with less profound computational background. b) It supports three performance evaluation criteria (e.g. number of DEPs, correlation coefficient between P-values and effect sizes, Area under the ROC curve) for users to review the final statistical results, which may guide the method selection for DEPs detection.

Dynamic regulation of N6,2'-O-dimethyladenosine (m6Am) in obesity

The prevalent m⁶Am mRNA cap modification was recently identified as a valid target for removal by the human obesity gene FTO along with the previously established m⁶A mRNA modification. However, the deposition and dynamics of m⁶Am in regulating obesity are unknown. Here, we investigate the liver m⁶A/m methylomes in mice fed on a high fat Western-diet and in ob/ob mice. We find that FTO levels are elevated in fat mice, and that genes which lost m⁶Am marking under obesity are overly downregulated, including the two fatty-acid-binding proteins FABP2, and FABP5. Furthermore, the cellular perturbation of FTO correspondingly affect protein levels of its targets. Notably, generally m⁶Am- but not m⁶A-methylated genes, are found to be highly enriched in metabolic processes. Finally, we deplete all m⁶A background via Mettl3 knockout, and unequivocally uncover the association of m⁶Am methylation with increased mRNA stability, translation efficiency, and higher protein expression. Together, these results strongly implicate a dynamic role for m⁶Am in obesity-related translation regulation.

Unraveling the Neuroprotective Effect of Tinospora cordifolia in a Parkinsonian Mouse Model through the Proteomics Approach

Stress-induced dopaminergic (DAergic) neuronal death in the midbrain region is the primary cause of Parkinson's disease (PD). Following the discovery of l-dopa, multiple drugs have been developed to improve the lifestyle of PD patients; however, none have been suitable for clinical use due to their multiple side effects. Tinospora cordifolia has been used in traditional medicines to treat neurodegenerative diseases. Previously, we reported the neuroprotective role of Tc via inhibition of NF-κB-associated proinflammatory cytokines against MPTP-intoxicated Parkinsonian mice. In the present study, we investigated the neuroprotective molecular mechanism of Tc in a rotenone (ROT)-intoxicated mouse model, using a proteomics approach. Mice were pretreated with Tc extract by oral administration, followed by ROT intoxication. Behavioral tests were performed to check motor functions of mice. Protein was isolated, and label-free quantification (LFQ) was carried out to identify differentially expressed protein (DEP) in control vs PD and PD vs treatment groups. Results were validated by qRT-PCR with the expression of target genes correlating with the proteomics data. In this study, we report 800 DEPs in control vs PD and 133 in PD vs treatment groups. In silico tools demonstrate significant enrichment of biochemical and molecular pathways with DEPs, which are known to be important for PD progression including mitochondrial gene expression, PD pathways, TGF-β signaling, and Alzheimer's disease. This study provides novel insights into the PD progression as well as new therapeutic targets. More importantly, it demonstrates that Tc can exert therapeutic effects by regulating multiple pathways, resulting in neuroprotection.

Analysis of the Aqueous Humor Proteome in Patients With Age-Related Macular Degeneration

Purpose

Age-related macular degeneration (AMD) is associated with altered gene and protein expression in the retina. We characterize the aqueous humor (AH) proteome in AMD to gain insight into the pathogenesis of the disease and identify potential biomarkers.

Methods

AH was collected from age and gender matched neovascular AMD (nvAMD; n = 10) patients and controls (n = 10). AH was pooled to create two samples (nvAMD and control), followed by intensity-based label-free quantification (MS1). Functional and bioinformatic analysis were then performed. A validation set (20 controls, 15 atrophic AMD and 15 nvAMD) was tested via multiplex ELISA for nine differentially expressed proteins according to the MS1 findings.

Results

MS1 identified 674 proteins in the AH. 239 proteins were upregulated in nvAMD (nvAMD/control > 2, peptide tags (PT) > 2), and 86 proteins were downregulated (nvAMD/control < 0.5, PT > 2). Functional analysis of proteins upregulated in AMD demonstrated enrichment for platelet degranulation (enrichment score (ES):28.1), negative regulation of endopeptidase activity (ES:18.8), cellular protein metabolic process (ES:11.8), epidermal growth factor-like domain (ES:10.3), sushi/SCR/CCP (ES:10.1), and complement/coagulation cascades (ES:9.2). AMD protein clusters were upregulated for 3/6 (χ2 < 0.05 compared to randomization). Validation via ELISA confirmed MS1 in 2/9 proteins (Clusterin and Serpin A4, P < 0.05), while 3/9 showed differential expression between aAMD and nvAMD (Clusterin, Serpin A4, and TF P < 0.05). Receiver operating characteristic curve calculation identified the area under the curve of 0.82 for clusterin as a biomarker for distinction of AMD.

Conclusions

AH proteomics in AMD patients identified several proteins and functional clusters with altered expression. Further research should confirm if these proteins may serve as biomarkers or therapeutic target for the disease.

The application of laboratory-based analytical tools and techniques for the quality assessment and improvement of commercial antivenoms used in the treatment of snakebite envenomation

Snakebite envenomation is a public health problem of high impact, particularly for the developing world. Antivenom, which contains whole or protease-digested immunoglobulin G, purified from the plasma of hyper-immunized animals (mainly horses), is the mainstay for the treatment of snakebite envenomation. The success of antivenom therapy depends upon its ability to abrogate or reduce the local and systemic toxicity of envenomation. In addition, antivenom administration must be safe for the patients. Therefore, antivenom manufacturers must ensure that these products are effective and safe in the treatment of envenomations. Antivenom efficacy and safety are determined by the physicochemical characteristics of formulations, purity of the immunoglobulin fragments and antibodies, presence of protein aggregates, endotoxin burden, preservative load, and batch to batch variation, as well as on the ability to neutralize the most important toxins of the venoms against which the antivenom is designed. In this context, recent studies have shown that laboratory-based simple analytical techniques, for example, size exclusion chromatography, sodium dodecyl sulphate polyacrylamide gel electrophoresis, mass spectrometry, immunological profiling including immuno-turbidimetry and enzyme-linked immunosorbent assays, Western blotting, immune-chromatographic technique coupled to mass spectrometry analysis, reverse-phase high performance liquid chromatography, spectrofluorometric analysis, in vitro neutralization of venom enzymatic activities, and other methodologies, can be applied for the assessment of antivenom quality, safety, stability, and efficacy. This article reviews the usefulness of different analytical techniques for the quality assessment of commercial antivenoms. It is suggested that these tests should be applied for screening the quality of commercial antivenoms before their preclinical and clinical assessment.

Characterization of the liver proteome in dairy cows experiencing negative energy balance at early lactation

Negative energy balance (NEB) is associated with metabolic disorders in early lactation dairy cows. Therefore, our objective was to characterize the liver proteome in cows experiencing either NEB or positive energy balance (PEB). Forty-two multiparous Holstein dairy cows were milked either 2 or 3 times daily for the first 30 days in milk (DIM) to alter EB, and were classified retrospectively as NEB (n = 18) or PEB (n = 22). Liver biopsies were collected from 10 cows (n = 5 from each milking frequency) at 17 ± 3 DIM (NEB, n = 6; PEB, n = 4). The liver proteome was characterized using label-free quantitative shotgun proteomics and Ingenuity Pathway Analysis used to identify key affected canonical pathways. Overall, 2741 proteins were identified, and 68 of those were differentially abundant (P ≤ 0.05 and FC ± 1.5). ENO3 (FC = 10.3, P < 0.01) and FABP5 (FC = -12.5, P = 0.045) were the most dramatically upregulated and downregulated proteins, respectively, in NEB cows. Numerous mitochondrial proteins (NDUFA5, NDUFS3, NDUFA6, COX7A2L, COX6C, and COA5) were differentially abundant. Canonical pathways associated with NEB were LPS/IL-1 mediated inhibition of RXR function, oxidative phosphorylation, and mitochondrial dysfunction. Additionally, cows experiencing NEB had less hepatic IL10 transcript abundance than PEB. Together, NEB was associated with altered hepatic inflammatory status, likely due to oxidative stress from mitochondrial dysfunction. SIGNIFICANCE: Our manuscript describes the associations of negative energy balance with the liver proteome in early lactation dairy cows, when metabolic stress and the incidence of diseases is increased. Specifically, we found associations of negative energy balance with shifts in hepatic protein abundance involved in fatty acid uptake, impaired anti-inflammatory responses, and mitochondrial dysfunction. Moving forward, differentially abundant proteins found in this study may be useful as either biological markers for disease or therapeutic targets to improve metabolic adaptations to lactation in postpartum dairy cattle.

Dioscorea Alata Tuber Proteome Analysis Uncovers Differentially Regulated Growth-associated Pathways of Tuber Development

During its life cycle, the Dioscorea tuber undergoes multiple morphological and biochemical changes. To gain a better understanding of the metabolic changes associated with tuber growth, a stage-specific gel-free proteome analysis of four distinct morphological stages namely germinating tuber (S1), degrading tuber (S2), new tuber formation (S3) and tuber maturation (S4) was done and validated by principal component analysis. A comprehensive data set identifying 78.2% of the total 3,681 proteins was generated. PANTHER and KEGG MAPPER revealed both expected (carbohydrate metabolism and redox regulation) and novel biological processes (transcription factors and hormonal regulation) characteristic for each developmental stage. Higher abundance of the enzymes of ascorbate-glutathione cycle and carbohydrate metabolism was detected during tuber germination (S1) and tuber formation stages (S3) in comparison with the mature tuber. The presence of ethylene biosynthesis components during tuber formation hints toward its probable role in postharvest shelf life. The data set comprehensively describes the proteome of Dioscorea tuber and provides growth-specific markers for tuber germination (ascorbate peroxidase, monodehydroascorbate reductase, invertase) and tuber formation (sucrose synthase), which were validated by enzyme activity assays and Western blotting. The study provides information that may influence the direction of research for improving the productivity of this under-utilized and largely neglected crop.

Benchmarking accuracy and precision of intensity-based absolute quantification of protein abundances in Saccharomyces cerevisiae

Protein quantification via label-free mass spectrometry (MS) has become an increasingly popular method for predicting genome-wide absolute protein abundances. A known caveat of this approach, however, is the poor technical reproducibility, that is, how consistent predictions are when the same sample is measured repeatedly. Here, we measured proteomics data for Saccharomyces cerevisiae with both biological and inter-batch technical triplicates, to analyze both accuracy and precision of protein quantification via MS. Moreover, we analyzed how these metrics vary when applying different methods for converting MS intensities to absolute protein abundances. We demonstrate that our simple normalization and rescaling approach can perform as accurately, yet more precisely, than methods which rely on external standards. Additionally, we show that inter-batch reproducibility is worse than biological reproducibility for all evaluated methods. These results offer a new benchmark for assessing MS data quality for protein quantification, while also underscoring current limitations in this approach.

Benchmarking Quantitative Performance in Label-Free Proteomics

Previous benchmarking studies have demonstrated the importance of instrument acquisition methodology and statistical analysis on quantitative performance in label-free proteomics. However, the effects of these parameters in combination with replicate number and false discovery rate (FDR) corrections are not known. Using a benchmarking standard, we systematically evaluated the combined impact of acquisition methodology, replicate number, statistical approach, and FDR corrections. These analyses reveal a complex interaction between these parameters that greatly impacts the quantitative fidelity of protein- and peptide-level quantification. At a high replicate number (n = 8), both data-dependent acquisition (DDA) and data-independent acquisition (DIA) methodologies yield accurate protein quantification across statistical approaches. However, at a low replicate number (n = 4), only DIA in combination with linear models for microarrays (LIMMA) and reproducibility-optimized test statistic (ROTS) produced a high level of quantitative fidelity. Quantitative accuracy at low replicates is also greatly impacted by FDR corrections, with Benjamini-Hochberg and Storey corrections yielding variable true positive rates for DDA workflows. For peptide quantification, replicate number and acquisition methodology are even more critical. A higher number of replicates in combination with DIA and LIMMA produce high quantitative fidelity, while DDA performs poorly regardless of replicate number or statistical approach. These results underscore the importance of pairing instrument acquisition methodology with the appropriate replicate number and statistical approach for optimal quantification performance.

Proteomic analysis of subcellular compartments containing disseminated alpha-synuclein seeds

The pathological form of a-synuclein (a-syn) is transmitted through neural circuits in the brains of Parkinson disease (PD) patients and amplifies misfolded a-syn, further forming intracellular deposits. However, the details of a-syn pre-formed fibrils (PFFs) transmission in vivo have not been fully elucidated. By inoculating Quantum dots (QD)-labeled a-syn PFFs (QD-a-syn PFFs) into the unilateral striatum, we detected QD-a-syn PFFs in brain homogenates obtained from the ipsilateral and contralateral sides of the inoculated site and further obtained QD-a-syn PFFs enriched-particles with fluorescence-activated organelle sorting. Proteomic analysis suggested that QD-a-syn PFFs-enriched particles in the contralateral side were associated with component proteins of synapse. In contrast, QD-a-syn PFFs-enriched particles in the ipsilateral side were associated with proteins belonging to ER components. Immunostaining of brain sections confirmed that QD-a-syn PFFs in the contralateral side were co-localized with synaptic vesicle marker proteins in the cortex and striatum. Additionally, QD-a-syn PFFs in the ipsilateral side were more co-localized with ER marker proteins compared to the contralateral side. These results correspond to proteomic analysis. This study provides potential candidates for the subcellular localization of a-syn PFFs in vivo during the dissemination phase of seeds. These subcellular compartments could be involved in the transmission of seeds.

ERBB2 drives YAP activation and EMT-like processes during cardiac regeneration

Cardiomyocyte loss after injury results in adverse remodelling and fibrosis, inevitably leading to heart failure. The ERBB2-Neuregulin and Hippo-YAP signalling pathways are key mediators of heart regeneration, yet the crosstalk between them is unclear. We demonstrate that transient overexpression of activated ERBB2 in cardiomyocytes (OE CMs) promotes cardiac regeneration in a heart failure model. OE CMs present an epithelial-mesenchymal transition (EMT)-like regenerative response manifested by cytoskeletal remodelling, junction dissolution, migration and extracellular matrix turnover. We identified YAP as a critical mediator of ERBB2 signalling. In OE CMs, YAP interacts with nuclear-envelope and cytoskeletal components, reflecting an altered mechanical state elicited by ERBB2. We identified two YAP-activating phosphorylations on S352 and S274 in OE CMs, which peak during metaphase, that are ERK dependent and Hippo independent. Viral overexpression of YAP phospho-mutants dampened the proliferative competence of OE CMs. Together, we reveal a potent ERBB2-mediated YAP mechanotransduction signalling, involving EMT-like characteristics, resulting in robust heart regeneration.

From classical to new generation approaches: An excursus of -omics methods for investigation of protein-protein interaction networks

Functional Proteomics aims to the identification of in vivo protein-protein interaction (PPI) in order to piece together protein complexes, and therefore, cell pathways involved in biological processes of interest. Over the years, proteomic approaches used for protein-protein interaction investigation have relied on classical biochemical protocols adapted to a global overview of protein-protein interactions, within so-called "interactomics" investigation. In particular, their coupling with advanced mass spectrometry instruments and innovative analytical methods led to make great strides in the PPIs investigation in proteomics. In this review, an overview of protein complexes purification strategies, from affinity purification approaches, including proximity-dependent labeling techniques and cross-linking strategy for the identification of transient interactions, to Blue Native Gel Electrophoresis (BN-PAGE) and Size Exclusion Chromatography (SEC) employed in the "complexome profiling", has been reported, giving a look to their developments, strengths and weakness and providing to readers several recent applications of each strategy. Moreover, a section dedicated to bioinformatic databases and platforms employed for protein networks analyses was also included.

PolySTest: Robust Statistical Testing of Proteomics Data with Missing Values Improves Detection of Biologically Relevant Features

Statistical testing remains one of the main challenges for high-confidence detection of differentially regulated proteins or peptides in large-scale quantitative proteomics experiments by mass spectrometry. Statistical tests need to be sufficiently robust to deal with experiment intrinsic data structures and variations and often also reduced feature coverage across different biological samples due to ubiquitous missing values. A robust statistical test provides accurate confidence scores of large-scale proteomics results, regardless of instrument platform, experimental protocol and software tools. However, the multitude of different combinations of experimental strategies, mass spectrometry techniques and informatics methods complicate the decision of choosing appropriate statistical approaches. We address this challenge by introducing PolySTest, a user-friendly web service for statistical testing, data browsing and data visualization. We introduce a new method, Miss test, that simultaneously tests for missingness and feature abundance, thereby complementing common statistical tests by rescuing otherwise discarded data features. We demonstrate that PolySTest with integrated Miss test achieves higher confidence and higher sensitivity for artificial and experimental proteomics data sets with known ground truth. Application of PolySTest to mass spectrometry based large-scale proteomics data obtained from differentiating muscle cells resulted in the rescue of 10-20% additional proteins in the identified molecular networks relevant to muscle differentiation. We conclude that PolySTest is a valuable addition to existing tools and instrument enhancements that improve coverage and depth of large-scale proteomics experiments. A fully functional demo version of PolySTest and Miss test is available via http://computproteomics.bmb.sdu.dk/Apps/PolySTest.

Proteomic Signatures of Corals from Thermodynamic Reefs

Unlike most parts of the world, coral reefs of Taiwan’s deep south have generally been spared from climate change-induced degradation. This has been linked to the oceanographically unique nature of Nanwan Bay, where intense upwelling occurs. Specifically, large-amplitude internal waves cause shifts in temperature of 6–9 °C over the course of several hours, and the resident corals not only thrive under such conditions, but they have also been shown to withstand multi-month laboratory incubations at experimentally elevated temperatures. To gain insight into the sub-cellular basis of acclimation to upwelling, proteins isolated from reef corals (Seriatopora hystrix) featured in laboratory-based reciprocal transplant studies in which corals from upwelling and non-upwelling control reefs (<20 km away) were exposed to stable or variable temperature regimes were analyzed via label-based proteomics (iTRAQ). Corals exposed to their “native” temperature conditions for seven days (1) demonstrated highest growth rates and (2) were most distinct from one another with respect to their protein signatures. The latter observation was driven by the fact that two Symbiodiniaceae lipid trafficking proteins, sec1a and sec34, were marginally up-regulated in corals exposed to their native temperature conditions. Alongside the marked degree of proteomic “site fidelity” documented, this dataset sheds light on the molecular mechanisms underlying acclimatization to thermodynamically extreme conditions in situ.

Focus on the spectra that matter by clustering of quantification data in shotgun proteomics

In shotgun proteomics, the analysis of label-free quantification experiments is typically limited by the identification rate and the noise level in the quantitative data. This generally causes a low sensitivity in differential expression analysis. Here, we propose a quantification-first approach for peptides that reverses the classical identification-first workflow, thereby preventing valuable information from being discarded in the identification stage. Specifically, we introduce a method, Quandenser, that applies unsupervised clustering on both MS1 and MS2 level to summarize all analytes of interest without assigning identities. This reduces search time due to the data reduction. We can now employ open modification and de novo searches to identify analytes of interest that would have gone unnoticed in traditional pipelines. Quandenser+Triqler outperforms the state-of-the-art method MaxQuant+Perseus, consistently reporting more differentially abundant proteins for all tested datasets. Software is available for all major operating systems at https://github.com/statisticalbiotechnology/quandenser, under Apache 2.0 license.

Proteomics-Based Approach Identifies Altered ER Domain Properties by ALS-Linked VAPB Mutation

An ER transmembrane protein, vesicle-associated membrane protein-associated protein B (VAPB), binds to several organelle-resident membrane proteins to mediate ER-organelle tethering. Mutation in amyotrophic lateral sclerosis (ALS) induces protein misfolding and aggregation, leading to ER disorganization. Gain or loss of function is suggested for VAPB mutation, however comprehensive study focusing on VAPB-ER domain has yet been performed. We here conducted proteomic characterization of the ER containing VAPB and its ALS-linked P56S mutant. For this purpose, we first optimized the proteomics of different ER domains immuno-isolated from cultured cells, and identified ER sheet- and tubule-specific proteomes. By using these as references, we found that VAPB-ER proteome had intermediate ER domain properties but its tubular property was specifically decreased by its mutation. Biochemical, immunofluorescence and proximity ligation assays suggested this was mediated by delocalization of VAPB from ER tubules. The VAPB-ER proteomics further suggested reduced incorporation of multiple proteins located in different organelles, which was confirmed by proximity ligation assay. Taken together, our proteomics-based approach indicates altered ER domain properties and impaired ER-organelle tethering by VAPB mutation.

Leucine improves α-amylase secretion through the general secretory signaling pathway in pancreatic acinar cells of dairy calves

The present study aimed to elucidate the mechanisms by which leucine impacts the secretion of pancreatic enzymes, especially amylase, by studying the proteomics profiles of pancreatic acinar (PA) cells from dairy cows. PA cells, the experimental model, were treated with four concentrations of leucine (0, 0.23, 0.45, and 0.90 mM). The abundance of different proteins in the four leucine treatment groups was detected. Label-free proteomic analysis enabled the identification of 1,906 proteins in all four treatment groups, and 1,350 of these proteins showed common expression across the groups. The primary effects of leucine supplementation were increased (P < 0.05) citrate synthase and ATPase activity, which enlarged the cytosolic ATP pool, and the upregulation of secretory protein 61 (Sec61) expression, which promoted protein secretion. In summary, these results suggest that leucine increases citrate synthase in the TCA cycle and ATPase activity and promotes the Sec signaling pathway to increase the exocrine function of PA cells.

Discovery of Interacting Proteins of ABA Receptor PYL5 via Covalent Chemical Capture

Abscisic acid (ABA) is a key phytohormone with diverse functions in plants, and its signal transduction is mainly mediated by ABA receptors termed PYR/PYL/RCARs (hereafter referred to as PYLs) through the PYLs-PP2Cs-SnRK2s regulatory systems. However, the model failed to account for the roles of some important known regulators of ABA physiology. Given the central role of PYLs in ABA signal transduction, we therefore speculated that ABA receptors PYLs might be involved in regulatory pathways other than PP2Cs. Thus, a comprehensive analysis of PYLs-interacting partners could greatly facilitate the identification of unknown regulatory pathways, advancing our knowledge of the ABA signaling mechanism. Herein, we present a strategy involving covalent chemical capture coupled with HPLC-MS/MS analysis, to profile PYL5-interacting partners in plant cell lysates. With this strategy, three new PYL5-interacting partners, ubiquitin receptor RAD23C, COP9 signalosome complex subunit 1 (CSN1), and cyclase-associated protein 1 (CAP1), along with their key binding sites with PYL5 were identified. Among these proteins, CAP1 was verified to interact with PYL5 both in vitro and in vivo. The discovery of a new PYL5 binding partner showed the versatility of covalent chemical cross-linking and laid the foundation for future efforts to further elucidate the ABA signaling mechanism.

Activity-Based Protein Profiling Identifies ATG4B as a Key Host Factor for Enterovirus 71 Proliferation

Virus-encoded proteases play diverse roles in the efficient replication of enterovirus 71 (EV71), which is the causative agent of human hand, foot, and mouth disease (HFMD). However, it is unclear how host proteases affect viral proliferation. Here, we designed activity-based probes (ABPs) based on an inhibitor of the main EV71 protease (3Cpro), which is responsible for the hydrolysis of the EV71 polyprotein, and successfully identified host candidates that bind to the ABPs. Among the candidates, the host cysteine protease autophagy-related protein 4 homolog B (ATG4B), a key component of the autophagy machinery, was demonstrated to hydrolytically process the substrate of EV71 3Cpro and had activity comparable to that of the viral protease. Genetic disruption of ATG4B confirmed that the enzyme is indispensable for viral proliferation in vivo Our results not only further the understanding of host-virus interactions in EV71 biology but also provide a sample for the usage of activity-based proteomics to reveal host-pathogen interactions.IMPORTANCE Enterovirus 71 (EV71), one of the major pathogens of human HFMD, has caused outbreaks worldwide. How EV71 efficiently assesses its life cycle with elaborate interactions with multiple host factors remains to be elucidated. In this work, we deconvoluted that the host ATG4B protein processes the viral polyprotein with its cysteine protease activity and helps EV71 replicate through a chemical biology strategy. Our results not only further the understanding of the EV71 life cycle but also provide a sample for the usage of activity-based proteomics to reveal host-pathogen interactions.

Unraveling proteome changes and potential regulatory proteins of bovine follicular Granulosa cells by mass spectrometry and multi-omics analysis

Background

In previous study, we performed next-gene sequencing to investigate the differentially expressed transcripts of bovine follicular granulosa cells (GCs) at dominant follicle (DF) and subordinate follicle (SF) stages during first follicular wave. Present study is designed to further identify the key regulatory proteins and signaling pathways associated with follicular development using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) and multi-omics data analysis approach.

Methods

DF and SF from three cattle were collected by daily ultrasonography. The GCs were isolated from each follicle, total proteins were digested by trypsin, and then proteomic analyzed via LC-MS/MS, respectively. Proteins identified were retrieved from Uniprot-COW fasta database, and differentially expressed proteins were used to functional enrichment and KEGG pathway analysis. Proteome data and transcriptome data obtained from previous studies were integrated.

Results

Total 3409 proteins were identified from 30,321 peptides (FDR ≤0.01) obtained from LC-MS/MS analysis and 259 of them were found to be differentially expressed at different stage of follicular development (fold Change > 2, P < 0.05). KEGG pathway analysis of proteome data revealed important signaling pathways associated with follicular development, multi-omics data analysis results showed 13 proteins were identified as being differentially expressed in DF versus SF.

Conclusions

This study represents the first investigation of transcriptome and proteome of bovine follicles and offers essential information for future investigation of DF and SF in cattle. It also will enrich the theory of animal follicular development.

Electronic supplementary material

The online version of this article (10.1186/s12953-019-0152-1) contains supplementary material, which is available to authorized users.

Proteome dataset of subcutaneous adipose tissue from postpartum cows treated with sodium salicylate

This article contains raw and processed data related to research published by Takiya et al. [1]. Literature have shown that treatment with the nonsteroidal anti-inflammatory agent sodium salicylate (SS) during the first days postpartum in dairy cows increased lactation performance [2], and tended to alter glucose metabolism [3]. Yet, the specific effects of systemic SS treatment on the proteome of the adipose tissue (AT) and on the inflammatory process in AT of postpartum cows is unknown. Subcutaneous AT samples were collected at 7 d of lactation from control cows (n = 5) and from cows treated with 2.3 g/L SS (n = 5) via drinking water during the first 7 d of lactation. Protein extraction and liquid chromatography-mass spectrometry were performed to obtain proteomics data. Differential abundance of proteins was determined through MS1 intensity based label-free method. Proteomics analysis generated a novel dataset consisted of 1422 proteins, 80 (5.6%) of which were differentially abundant [fold change ± 1.5, P < 0.05 2-way ANOVA] when comparing control and SS-treated cows. The present dataset of subcutaneous AT proteome from postpartum dairy cows treated with SS can be used as a reference for any research involving nonsteroidal anti-inflammatory agent treatment in dairy cows or in comparative research between species.

CSNAP, the smallest CSN subunit, modulates proteostasis through cullin-RING ubiquitin ligases

The cullin-RING ubiquitin E3 ligase (CRL) family consists of ~250 complexes that catalyze ubiquitylation of proteins to achieve cellular regulation. All CRLs are inhibited by the COP9 signalosome complex (CSN) through both enzymatic (deneddylation) and nonenzymatic (steric) mechanisms. The relative contribution of these two mechanisms is unclear. Here, we decouple the mechanisms using CSNAP, the recently discovered ninth subunit of the CSN. We find that CSNAP reduces the affinity of CSN toward CRL complexes. Removing CSNAP does not affect deneddylation, but leads to global effects on the CRL, causing altered reproductive capacity, suppressed DNA damage response, and delayed cell cycle progression. Thus, although CSNAP is only 2% of the CSN mass, it plays a critical role in the steric regulation of CRLs by the CSN.

Activation of Insulin Signaling in Adipocytes and Myotubes by Sarcopoterium Spinosum Extract

Sarcopoterium spinosum (S. spinosum) is a medicinal plant, traditionally used as an antidiabetic remedy. Previous studies demonstrated its beneficial properties in the treatment of insulin resistance. The aim of this study was to further clarify the effect of S. spinosum extract (SSE) on insulin signaling. Phosphoproteomic analysis, performed in 3T3-L1 adipocytes treated with SSE, revealed the activation of insulin receptor pathways. SSE increased Glut4-facilitated glucose uptake in adipocytes, with an additive effect between SSE and insulin. While the maximal effect of insulin on glucose uptake was found at days 15–16 of differentiation, SSE-induced glucose uptake was found at an earlier stage of differentiation. Inhibition of PI3K and Akt blocked SSE-dependent glucose uptake. Western blot analysis, performed on 3T3-L1 adipocytes and L6 myotubes, showed that in contrast to insulin action, Akt was only marginally phosphorylated by SSE. Furthermore, GSK3β and PRAS40 phosphorylation as well as glucose uptake were increased by the extract. SSE also induced the phosphorylation of ERK similar to insulin. In conclusion, SSE activates insulin signaling, although the upstream event mediating its effects should be further clarified. Identifying the active molecules in SSE may lead to the development of new agents for the treatment of insulin resistance.

Varroa chemosensory proteins: some are conserved across Arthropoda but others are arachnid specific

The tight synchronization between the life cycle of the obligatory parasitic mite Varroa destructor (Varroa) and its host, the honeybee, is mediated by honeybee chemical stimuli. These stimuli are mainly perceived by a pit organ located on the distal part of the mite's foreleg. In the present study, we searched for Varroa chemosensory molecular components by comparing transcriptomic and proteomic profiles between forelegs from different physiological stages, and rear legs. In general, a comparative transcriptomic analysis showed a clear separation of the expression profiles between the rear legs and the three groups of forelegs (phoretic, reproductive and tray-collected mites). Most of the differentially expressed transcripts and proteins in the mite's foreleg were previously uncharacterized. Using a conserved domain approach, we identified 45 transcripts with known chemosensory domains belonging to seven chemosensory protein families, of which 14 were significantly upregulated in the mite's forelegs when compared to rear legs. These are soluble and membrane bound proteins, including the somewhat ignored receptors of degenerin/epithelial Na+ channels and transient receptor potentials. Phylogenetic clustering and expression profiles of the putative chemosensory proteins suggest their role in chemosensation and shed light on the evolution of these proteins in Chelicerata.

Spectral Clustering Improves Label-Free Quantification of Low-Abundant Proteins

Label-free quantification has become a common-practice in many mass spectrometry-based proteomics experiments. In recent years, we and others have shown that spectral clustering can considerably improve the analysis of (primarily large-scale) proteomics data sets. Here we show that spectral clustering can be used to infer additional peptide-spectrum matches and improve the quality of label-free quantitative proteomics data in data sets also containing only tens of MS runs. We analyzed four well-known public benchmark data sets that represent different experimental settings using spectral counting and peak intensity based label-free quantification. In both approaches, the additionally inferred peptide-spectrum matches through our spectra-cluster algorithm improved the detectability of low abundant proteins while increasing the accuracy of the derived quantitative data, without increasing the data sets' noise. Additionally, we developed a Proteome Discoverer node for our spectra-cluster algorithm which allows anyone to rebuild our proposed pipeline using the free version of Proteome Discoverer.

Chlorophyll catabolism precedes changes in chloroplast structure and proteome during leaf senescence

The earliest visual changes of leaf senescence occur in the chloroplast as chlorophyll is degraded and photosynthesis declines. Yet, a comprehensive understanding of the sequence of catabolic events occurring in chloroplasts during natural leaf senescence is still missing. Here, we combined confocal and electron microscopy together with proteomics and biochemistry to follow structural and molecular changes during Arabidopsis leaf senescence. We observed that initiation of chlorophyll catabolism precedes other breakdown processes. Chloroplast size, stacking of thylakoids, and efficiency of PSII remain stable until late stages of senescence, whereas the number and size of plastoglobules increase. Unlike catabolic enzymes, whose level increase, the level of most proteins decreases during senescence, and chloroplast proteins are overrepresented among these. However, the rate of their disappearance is variable, mostly uncoordinated and independent of their inherent stability during earlier developmental stages. Unexpectedly, degradation of chlorophyll-binding proteins lags behind chlorophyll catabolism. Autophagy and vacuole proteins are retained at relatively high levels, highlighting the role of extra-plastidic degradation processes especially in late stages of senescence. The observation that chlorophyll catabolism precedes all other catabolic events may suggest that this process enables or signals further catabolic processes in chloroplasts.

Characterization of the endocannabinoid system in subcutaneous adipose tissue in periparturient dairy cows and its association to metabolic profiles

Adipose tissue (AT) plays a major role in metabolic adaptations in postpartum (PP) dairy cows. The endocannabinoid (eCB) system is a key regulator of metabolism and energy homeostasis; however, information about this system in ruminants is scarce. Therefore, this work aimed to assess the eCB system in subcutaneous AT, and to determine its relation to the metabolic profile in peripartum cows. Biopsies of AT were performed at 14 d prepartum, and 4 and 30 d PP from 18 multiparous peripartum cows. Cows were categorized retrospectively according to those with high body weight (BW) loss (HWL, 8.5 ± 1.7% BW loss) or low body weight loss (LWL, 2.9 ± 2.5% BW loss) during the first month PP. The HWL had higher plasma non-esterified fatty acids and a lower insulin/glucagon ratio PP than did LWL. Two-fold elevated AT levels of the main eCBs, N-arachidonoylethanolamine (AEA) and 2-arachidonoylglycerol (2-AG), were found 4 d PP compared with prepartum in HWL, but not in LWL cows. AT levels of the eCB-like molecules oleoylethanolamide, palmitoylethanolamide, and of arachidonic acid were elevated PP compared with prepartum in all cows. The abundance of monoglyceride lipase (MGLL), the 2-AG degrading enzyme, was lower in HWL vs. LWL AT PP. The relative gene expression of the cannabinoid receptors CNR1 and CNR2 in AT tended to be higher in HWL vs. LWL PP. Proteomic analysis of AT showed an enrichment of the inflammatory pathways’ acute phase signaling and complement system in HWL vs. LWL cows PP. In summary, eCB levels in AT were elevated at the onset of lactation as part of the metabolic adaptations in PP dairy cows. Furthermore, activating the eCB system in AT is most likely associated with a metabolic response of greater BW loss, lipolysis, and AT inflammation in PP dairy cows.

Neutralizing Gatad2a-Chd4-Mbd3/NuRD Complex Facilitates Deterministic Induction of Naive Pluripotency

Mbd3, a member of nucleosome remodeling and deacetylase (NuRD) co-repressor complex, was previously identified as an inhibitor for deterministic induced pluripotent stem cell (iPSC) reprogramming, where up to 100% of donor cells successfully complete the process. NuRD can assume multiple mutually exclusive conformations, and it remains unclear whether this deterministic phenotype can be attributed to a specific Mbd3/NuRD subcomplex. Moreover, since complete ablation of Mbd3 blocks somatic cell proliferation, we aimed to explore functionally relevant alternative ways to neutralize Mbd3-dependent NuRD activity. We identify Gatad2a, a NuRD-specific subunit, whose complete deletion specifically disrupts Mbd3/NuRD repressive activity on the pluripotency circuitry during iPSC differentiation and reprogramming without ablating somatic cell proliferation. Inhibition of Gatad2a facilitates deterministic murine iPSC reprogramming within 8 days. We validate a distinct molecular axis, Gatad2a-Chd4-Mbd3, within Mbd3/NuRD as being critical for blocking reestablishment of naive pluripotency and further highlight signaling-dependent and post-translational modifications of Mbd3/NuRD that influence its interactions and assembly.

Integrated Omics: Tools, Advances, and Future Approaches

With the rapid adoption of high-throughput omic approaches to analyze biological samples such as genomics, transcriptomics, proteomics, and metabolomics, each analysis can generate tera- to peta-byte sized data files on a daily basis. These data file sizes, together with differences in nomenclature among these data types, make the integration of these multi-dimensional omics data into biologically meaningful context challenging. Variously named as integrated omics, multi-omics, poly-omics, trans-omics, pan-omics, or shortened to just 'omics', the challenges include differences in data cleaning, normalization, biomolecule identification, data dimensionality reduction, biological contextualization, statistical validation, data storage and handling, sharing, and data archiving. The ultimate goal is towards the holistic realization of a 'systems biology' understanding of the biological question in hand. Commonly used approaches in these efforts are currently limited by the 3 i's - integration, interpretation, and insights. Post integration, these very large datasets aim to yield unprecedented views of cellular systems at exquisite resolution for transformative insights into processes, events, and diseases through various computational and informatics frameworks. With the continued reduction in costs and processing time for sample analyses, and increasing types of omics datasets generated such as glycomics, lipidomics, microbiomics, and phenomics, an increasing number of scientists in this interdisciplinary domain of bioinformatics face these challenges. We discuss recent approaches, existing tools, and potential caveats in the integration of omics datasets for development of standardized analytical pipelines that could be adopted by the global omics research community.

Updates on resources, software tools, and databases for plant proteomics in 2016-2017

Proteomics data processing, annotation, and analysis can often lead to major hurdles in large-scale high-throughput bottom-up proteomics experiments. Given the recent rise in protein-based big datasets being generated, efforts in in silico tool development occurrences have had an unprecedented increase; so much so, that it has become increasingly difficult to keep track of all the advances in a particular academic year. However, these tools benefit the plant proteomics community in circumventing critical issues in data analysis and visualization, as these continually developing open-source and community-developed tools hold potential in future research efforts. This review will aim to introduce and summarize more than 50 software tools, databases, and resources developed and published during 2016-2017 under the following categories: tools for data pre-processing and analysis, statistical analysis tools, peptide identification tools, databases and spectral libraries, and data visualization and interpretation tools. Intended for a well-informed proteomics community, finally, efforts in data archiving and validation datasets for the community will be discussed as well. Additionally, the author delineates the current and most commonly used proteomics tools in order to introduce novice readers to this -omics discovery platform.

DJ-1 based peptide, ND-13, promote functional recovery in mouse model of focal ischemic injury

Stroke is a leading cause of death worldwide and inflicts serious long-term damage and disability. The vasoconstrictor Endothelin-1, presenting long-term neurological deficits associated with excitotoxicity and oxidative stress is being increasingly used to induce focal ischemic injury as a model of stroke. A DJ-1 based peptide named ND-13 was shown to protect against glutamate toxicity, neurotoxic insults and oxidative stress in various animal models. Here we focus on the benefits of treatment with ND-13 on the functional outcome of focal ischemic injury. Wild type C57BL/6 mice treated with ND-13, after ischemic induction in this model, showed significant improvement in motor function, including improved body balance and motor coordination, and decreased motor asymmetry. We found that DJ-1 knockout mice are more sensitive to Endothelin-1 ischemic insult than wild type mice, contributing thereby additional evidence to the widely reported relevance of DJ-1 in neuroprotection. Furthermore, treatment of DJ-1 knockout mice with ND-13, following Endothelin-1 induced ischemia, resulted in significant improvement in motor functions, suggesting that ND-13 provides compensation for DJ-1 deficits. These preliminary results demonstrate a possible basis for clinical application of the ND-13 peptide to enhance neuroprotection in stroke patients.

The proteomic response of the reef coral Pocillopora acuta to experimentally elevated temperatures

Although most reef-building corals live near the upper threshold of their thermotolerance, some scleractinians are resilient to temperature increases. For instance, Pocillopora acuta specimens from an upwelling habitat in Southern Taiwan survived a nine-month experimental exposure to 30°C, a temperature hypothesized to induce stress. To gain a greater understanding of the molecular pathways underlying such high-temperature acclimation, the protein profiles of experimental controls incubated at 27°C were compared to those of conspecific P. acuta specimens exposed to 30°C for two, four, or eight weeks, and differentially concentrated proteins (DCPs) were removed from the gels and sequenced with mass spectrometry. Sixty unique DCPs were uncovered across both eukaryotic compartments of the P. acuta-dinoflagellate (genus Symbiodinium) mutualism, and Symbiodinium were more responsive to high temperature at the protein-level than the coral hosts in which they resided at the two-week sampling time. Furthermore, proteins involved in the stress response were more likely to be documented at different cellular concentrations across temperature treatments in Symbiodinium, whereas the temperature-sensitive host coral proteome featured numerous proteins involved in cytoskeletal structure, immunity, and metabolism. These proteome-scale data suggest that the coral host and its intracellular dinoflagellates have differing strategies for acclimating to elevated temperatures.

Identification of seipin-linked factors that act as determinants of a lipid droplet subpopulation

Functional heterogeneity within the lipid droplet (LD) pool of a single cell has been observed, yet the underlying mechanisms remain enigmatic. Here, we report on identification of a specialized LD subpopulation characterized by a unique proteome and a defined geographical location at the nucleus-vacuole junction contact site. In search for factors determining identity of these LDs, we screened ∼6,000 yeast mutants for loss of targeting of the subpopulation marker Pdr16 and identified Ldo45 (LD organization protein of 45 kD) as a crucial targeting determinant. Ldo45 is the product of a splicing event connecting two adjacent genes (YMR147W and YMR148W/OSW5/LDO16). We show that Ldo proteins cooperate with the LD biogenesis component seipin and establish LD identity by defining positioning and surface-protein composition. Our studies suggest a mechanism to establish functional differentiation of organelles, opening the door to better understanding of metabolic decisions in cells.