Mapping and analyzing the human liver proteome: progress and potential

Introduction: The liver is an important organ in humans. Hepatocellular carcinoma (HCC) is one of the deadliest cancers in the world. Progress in the Human Liver Proteome Project (HLPP) has improved understanding of the liver and the liver cancer proteome.

Areas covered: Here, we summarize the recent progress in liver proteome modification profiles, proteomic studies in liver cancer, proteomic study in the search for novel liver cancer biomarkers and drug targets, and progress of the Chromosome Centric Human Proteome Project (CHPP) in the past five years in the Institutes of Biomedical Sciences (IBS) of Fudan University.

Expert commentary: Recent advances and findings discussed here provide great promise of improving the outcome of patients with liver cancer.     

Adsorption of heavy metal from aqueous solution by dehydrated root powder of long-root Eichhornia crassipes

The root powder of long-root Eichhornia crassipes, as a new kind of biodegradable adsorbent, has been tested for aqueous adsorption of Pb, Zn, Cu, and Cd. From FT-IR, we found that the absorption peaks of phosphorous compounds, carbonyl, and nitrogenous compounds displayed obvious changes before and after adsorption which illustrated that plant characteristics may play a role in binding with metals. Surface properties and morphology of the root powders have been characterized by means of SEM and BET. Energy spectrum analysis showed that the metals were adsorbed on root powders after adsorption. Then, optimum quantity of powder, pH values, and metal ion concentrations in single-system and multi-system were detected to discuss the characteristics and mechanisms of metal adsorption. Freundlich model and the second-order kinetics equation could well describe the adsorption of heavy metals in single-metal system. The adsorption of Pb, Zn, and Cd in the multi-metal system decreased with the concentration increased. At last, competitive adsorption of every two metals on root powder proved that Cu and Pb had suppressed the adsorption performance of Cd and Zn.     

Regulating the Skin Permeation Rate of Escitalopram by Ion-pair Formation with Organic Acids

In order to regulate the skin permeation rate (flux) of escitalopram (ESP), ion-pair strategy was used in our work. Five organic acids with different physicochemical properties, benzoic acid (BA), ibuprofen (IB), salicylic acid (SA), benzenesulfonic acid (BSA), and p-aminobenzoic acid (PABA), were employed as counter-ions to regulate the permeation rate of ESP across the rabbit abdominal skin in vitro. The interaction between ESP and organic acids was characterized by FTIR and ¹³C NMR spectroscopy. Results showed that all organic acids investigated in this study performed a controlling effect on ESP flux. To further analyze the factors concerned with the permeation capability of ESP-acid complex, a multiple linear regression model was used. It is concluded that the steady-state flux (J) of ESP-acid complexes had a positive correlation with log K _o/w (the n-octanol/water partition coefficient of ion-pair complex) and pK _a (the acidity of organic acid counter-ion), but a negative correlation with MW (the molecular weight of ion-pair complex). The logK _o/w of ion-pair complex is the primary one in all the factors that influence the skin permeation rate of ESP. The results demonstrated that organic acid with appropriate physicochemical properties can be considered as suitable candidate for the transdermal drug delivery of escitalopram.     

FoxO1 antagonist suppresses autophagy and lipid droplet growth in adipocytes

Obesity and related metabolic disorders constitute one of the most pressing heath concerns worldwide. Increased adiposity is linked to autophagy upregulation in adipose tissues. However, it is unknown how autophagy is upregulated and contributes to aberrant adiposity. Here we show a FoxO1-autophagy-FSP27 axis that regulates adipogenesis and lipid droplet (LD) growth in adipocytes. Adipocyte differentiation was associated with upregulation of autophagy and fat specific protein 27 (FSP27), a key regulator of adipocyte maturation and expansion by promoting LD formation and growth. However, FoxO1 specific inhibitor AS1842856 potently suppressed autophagy, FSP27 expression, and adipocyte differentiation. In terminally differentiated adipocytes, AS1842856 significantly reduced FSP27 level and LD size, which was recapitulated by autophagy inhibitors (bafilomycin-A1 and leupeptin, BL). Similarly, AS1842856 and BL dampened autophagy activity and FSP27 expression in explant cultures of white adipose tissue. To our knowledge, this is the first study addressing FoxO1 in the regulation of adipose autophagy, shedding light on the mechanism of increased autophagy and adiposity in obese individuals. Given that adipogenesis and adipocyte expansion contribute to aberrant adiposity, targeting the FoxO1-autophagy-FSP27 axis may lead to new anti-obesity options.     

MASH Suite Pro: A Comprehensive Software Tool for Top-Down Proteomics

Top-down mass spectrometry (MS)-based proteomics is arguably a disruptive technology for the comprehensive analysis of all proteoforms arising from genetic variation, alternative splicing, and posttranslational modifications (PTMs). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for data analysis in bottom-up proteomics, the data analysis tools in top-down proteomics remain underdeveloped. Moreover, despite recent efforts to develop algorithms and tools for the deconvolution of top-down high-resolution mass spectra and the identification of proteins from complex mixtures, a multifunctional software platform, which allows for the identification, quantitation, and characterization of proteoforms with visual validation, is still lacking. Herein, we have developed MASH Suite Pro, a comprehensive software tool for top-down proteomics with multifaceted functionality. MASH Suite Pro is capable of processing high-resolution MS and tandem MS (MS/MS) data using two deconvolution algorithms to optimize protein identification results. In addition, MASH Suite Pro allows for the characterization of PTMs and sequence variations, as well as the relative quantitation of multiple proteoforms in different experimental conditions. The program also provides visualization components for validation and correction of the computational outputs. Furthermore, MASH Suite Pro facilitates data reporting and presentation via direct output of the graphics. Thus, MASH Suite Pro significantly simplifies and speeds up the interpretation of high-resolution top-down proteomics data by integrating tools for protein identification, quantitation, characterization, and visual validation into a customizable and user-friendly interface. We envision that MASH Suite Pro will play an integral role in advancing the burgeoning field of top-down proteomics.With well-developed algorithms and computational tools for mass spectrometry (MS)¹ data analysis, peptide-based bottom-up proteomics has gained considerable popularity in the field of systems biology (1–9). Nevertheless, the bottom-up approach is suboptimal for the analysis of protein posttranslational modifications (PTMs) and sequence variants as a result of protein digestion (10). Alternatively, the protein-based top-down proteomics approach analyzes intact proteins, which provides a “bird''s eye” view of all proteoforms (11), including those arising from sequence variations, alternative splicing, and diverse PTMs, making it a disruptive technology for the comprehensive analysis of proteoforms (12–24). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for processing data from bottom-up proteomics experiments, the data analysis tools in top-down proteomics remain underdeveloped.The initial step in the analysis of top-down proteomics data is deconvolution of high-resolution mass and tandem mass spectra. Thorough high-resolution analysis of spectra by horn (THRASH), which was the first algorithm developed for the deconvolution of high-resolution mass spectra (25), is still widely used. THRASH automatically detects and evaluates individual isotopomer envelopes by comparing the experimental isotopomer envelope with a theoretical envelope and reporting those that score higher than a user-defined threshold. Another commonly used algorithm, MS-Deconv, utilizes a combinatorial approach to address the difficulty of grouping MS peaks from overlapping isotopomer envelopes (26). Recently, UniDec, which employs a Bayesian approach to separate mass and charge dimensions (27), can also be applied to the deconvolution of high-resolution spectra. Although these algorithms assist in data processing, unfortunately, the deconvolution results often contain a considerable amount of misassigned peaks as a consequence of the complexity of the high-resolution MS and MS/MS data generated in top-down proteomics experiments. Errors such as these can undermine the accuracy of protein identification and PTM localization and, thus, necessitate the implementation of visual components that allow for the validation and manual correction of the computational outputs.Following spectral deconvolution, a typical top-down proteomics workflow incorporates identification, quantitation, and characterization of proteoforms; however, most of the recently developed data analysis tools for top-down proteomics, including ProSightPC (28, 29), Mascot Top Down (also known as Big-Mascot) (30), MS-TopDown (31), and MS-Align+ (32), focus almost exclusively on protein identification. ProSightPC was the first software tool specifically developed for top-down protein identification. This software utilizes “shotgun annotated” databases (33) that include all possible proteoforms containing user-defined modifications. Consequently, ProSightPC is not optimized for identifying PTMs that are not defined by the user(s). Additionally, the inclusion of all possible modified forms within the database dramatically increases the size of the database and, thus, limits the search speed (32). Mascot Top Down (30) is based on standard Mascot but enables database searching using a higher mass limit for the precursor ions (up to 110 kDa), which allows for the identification of intact proteins. Protein identification using Mascot Top Down is fundamentally similar to that used in bottom-up proteomics (34), and, therefore, it is somewhat limited in terms of identifying unexpected PTMs. MS-TopDown (31) employs the spectral alignment algorithm (35), which matches the top-down tandem mass spectra to proteins in the database without prior knowledge of the PTMs. Nevertheless, MS-TopDown lacks statistical evaluation of the search results and performs slowly when searching against large databases. MS-Align+ also utilizes spectral alignment for top-down protein identification (32). It is capable of identifying unexpected PTMs and allows for efficient filtering of candidate proteins when the top-down spectra are searched against a large protein database. MS-Align+ also provides statistical evaluation for the selection of proteoform spectrum match (PrSM) with high confidence. More recently, Top-Down Mass Spectrometry Based Proteoform Identification and Characterization (TopPIC) was developed (http://proteomics.informatics.iupui.edu/software/toppic/index.html). TopPIC is an updated version of MS-Align+ with increased spectral alignment speed and reduced computing requirements. In addition, MSPathFinder, developed by Kim et al., also allows for the rapid identification of proteins from top-down tandem mass spectra (http://omics.pnl.gov/software/mspathfinder) using spectral alignment. Although software tools employing spectral alignment, such as MS-Align+ and MSPathFinder, are particularly useful for top-down protein identification, these programs operate using command line, making them difficult to use for those with limited knowledge of command syntax.Recently, new software tools have been developed for proteoform characterization (36, 37). Our group previously developed MASH Suite, a user-friendly interface for the processing, visualization, and validation of high-resolution MS and MS/MS data (36). Another software tool, ProSight Lite, developed recently by the Kelleher group (37), also allows characterization of protein PTMs. However, both of these software tools require prior knowledge of the protein sequence for the effective localization of PTMs. In addition, both software tools cannot process data from liquid chromatography (LC)-MS and LC-MS/MS experiments, which limits their usefulness in large-scale top-down proteomics. Thus, despite these recent efforts, a multifunctional software platform enabling identification, quantitation, and characterization of proteins from top-down spectra, as well as visual validation and data correction, is still lacking.Herein, we report the development of MASH Suite Pro, an integrated software platform, designed to incorporate tools for protein identification, quantitation, and characterization into a single comprehensive package for the analysis of top-down proteomics data. This program contains a user-friendly customizable interface similar to the previously developed MASH Suite (36) but also has a number of new capabilities, including the ability to handle complex proteomics datasets from LC-MS and LC-MS/MS experiments, as well as the ability to identify unknown proteins and PTMs using MS-Align+ (32). Importantly, MASH Suite Pro also provides visualization components for the validation and correction of the computational outputs, which ensures accurate and reliable deconvolution of the spectra and localization of PTMs and sequence variations.     

High glucose concentration induces endothelial cell proliferation by regulating cyclin‐D2‐related miR‐98

Cyclin D2 is involved in the pathology of vascular complications of type 2 diabetes mellitus (T2DM). This study investigated the role of cyclin‐D2‐regulated miRNAs in endothelial cell proliferation of T2DM. Results showed that higher glucose concentration (4.5 g/l) significantly promoted the proliferation of rat aortic endothelial cells (RAOECs), and significantly increased the expression of cyclin D2 and phosphorylation of retinoblastoma 1 (p‐RB1) in RAOECs compared with those under low glucose concentration. The cyclin D2‐3′ untranslated region is targeted by miR‐98, as demonstrated by miRNA analysis software. Western blot also confirmed that cyclin D2 and p‐RB1 expression was regulated by miR‐98. The results indicated that miR‐98 treatment can induce RAOEC apoptosis. The suppression of RAOEC growth by miR‐98 might be related to regulation of Bcl‐2, Bax and Caspase 9 expression. Furthermore, the expression levels of miR‐98 decreased in 4.5 g/l glucose‐treated cells compared with those treated by low glucose concentration. Similarly, the expression of miR‐98 significantly decreased in aortas of established streptozotocin (STZ)‐induced diabetic rat model compared with that in control rats; but cyclin D2 and p‐RB1 levels remarkably increased in aortas of STZ‐induced diabetic rats compared with those in healthy control rats. In conclusion, this study demonstrated that high glucose concentration induces cyclin D2 up‐regulation and miR‐98 down‐regulation in the RAOECs. By regulating cyclin D2, miR‐98 can inhibit human endothelial cell growth, thereby providing novel therapeutic targets for vascular complication of T2DM.