Integration of protein sequence and protein-protein interaction data by hypergraph learning to identify novel protein complexes.

Protein-protein interactions (PPIs) are the basis of many important biological processes, with protein complexes being the key forms implementing these interactions. Understanding protein complexes and their functions is critical for elucidating mechanisms of life processes, disease diagnosis and treatment and drug development. However, experimental methods for identifying protein complexes have many limitations. Therefore, it is necessary to use computational methods to predict protein complexes. Protein sequences can indicate the structure and biological functions of proteins, while also determining their binding abilities with other proteins, influencing the formation of protein complexes. Integrating these characteristics to predict protein complexes is very promising, but currently there is no effective framework that can utilize both protein sequence and PPI network topology for complex prediction. To address this challenge, we have developed HyperGraphComplex, a method based on hypergraph variational autoencoder that can capture expressive features from protein sequences without feature engineering, while also considering topological properties in PPI networks, to predict protein complexes. Experiment results demonstrated that HyperGraphComplex achieves satisfactory predictive performance when compared with state-of-art methods. Further bioinformatics analysis shows that the predicted protein complexes have similar attributes to known ones. Moreover, case studies corroborated the remarkable predictive capability of our model in identifying protein complexes, including 3 that were not only experimentally validated by recent studies but also exhibited high-confidence structural predictions from AlphaFold-Multimer. We believe that the HyperGraphComplex algorithm and our provided proteome-wide high-confidence protein complex prediction dataset will help elucidate how proteins regulate cellular processes in the form of complexes, and facilitate disease diagnosis and treatment and drug development. Source codes are available at https://github.com/LiDlab/HyperGraphComplex.

Identification of Proteome-Based Immune Subtypes of Early Hepatocellular Carcinoma and Analysis of Potential Metabolic Drivers.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, ranking fourth in frequency. The relationship between metabolic reprogramming and immune infiltration has been identified as having a crucial impact on HCC progression. However, a deeper understanding of the interplay between the immune system and metabolism in the HCC microenvironment is required. In this study, we used a proteomic dataset to identify three immune subtypes (IM1-IM3) in HCC, each of which has distinctive clinical, immune, and metabolic characteristics. Among these subtypes, IM3 was found to have the poorest prognosis, with the highest levels of immune infiltration and T-cell exhaustion. Furthermore, IM3 showed elevated glycolysis and reduced bile acid metabolism, which was strongly correlated with CD8 T cell exhaustion and regulatory T cell accumulation. Our study presents the proteomic immune stratification of HCC, revealing the possible link between immune cells and reprogramming of HCC glycolysis and bile acid metabolism, which may be a viable therapeutic strategy to improve HCC immunotherapy.

UbiBrowser 2.0: a comprehensive resource for proteome-wide known and predicted ubiquitin ligase/deubiquitinase-substrate interactions in eukaryotic species.

As an important post-translational modification, ubiquitination mediates ∼80% of protein degradation in eukaryotes. The degree of protein ubiquitination is tightly determined by the delicate balance between specific ubiquitin ligase (E3)-mediated ubiquitination and deubiquitinase-mediated deubiquitination. In 2017, we developed UbiBrowser 1.0, which is an integrated database for predicted human proteome-wide E3-substrate interactions. Here, to meet the urgent requirement of proteome-wide E3/deubiquitinase-substrate interactions (ESIs/DSIs) in multiple organisms, we updated UbiBrowser to version 2.0 (http://ubibrowser.ncpsb.org.cn). Using an improved protocol, we collected 4068/967 known ESIs/DSIs by manual curation, and we predicted about 2.2 million highly confident ESIs/DSIs in 39 organisms, with >210-fold increase in total data volume. In addition, we made several new features in the updated version: (i) it allows exploring proteins' upstream E3 ligases and deubiquitinases simultaneously; (ii) it has significantly increased species coverage; (iii) it presents a uniform confidence scoring system to rank predicted ESIs/DSIs. To facilitate the usage of UbiBrowser 2.0, we also redesigned the web interface for exploring these known and predicted ESIs/DSIs, and added functions of 'Browse', 'Download' and 'Application Programming Interface'. We believe that UbiBrowser 2.0, as a discovery tool, will contribute to the study of protein ubiquitination and the development of drug targets for complex diseases.

Human umbilical cord-derived mesenchymal stem cell transplantation supplemented with curcumin improves the outcomes of ischemic stroke via AKT/GSK-3ß/ß-TrCP/Nrf2 axis.

BACKGROUND: Human umbilical cord-derived mesenchymal stem cell (hUC-MSC) engraftment is a promising therapy for acute ischemic stroke (AIS). However, the harsh ischemic microenvironment limits the therapeutic efficacy of hUC-MSC therapy. Curcumin is an anti-inflammatory agent that could improve inflammatory microenvironment. However, whether it enhances the neuroprotective efficacy of hUC-MSC transplantation is still unknown. In the present study, we investigated the therapeutic efficacy and the possible mechanism of combined curcumin and hUC-MSC treatment in AIS. METHODS: Middle cerebral artery occlusion (MCAO) mice and oxygen glucose deprivation (OGD) microglia were administrated hUC-MSCs with or without curcumin. Neurological deficits assessment, brain water content and TTC were used to assess the therapeutic effects of combined treatment. To elucidate the mechanism, MCAO mice and OGD microglia were treated with AKT inhibitor MK2206, GSK3ß activator sodium nitroprusside (SNP), GSK3ß inhibitor TDZD-8 and Nrf2 gene knockout were used. Immunofluorescence, flow cytometric analysis, WB and RT-PCR were used to evaluate the microglia polarization and the expression of typical oxidative mediators, inflammatory cytokines and the AKT/GSK-3ß/ß-TrCP/Nrf2 pathway protein. RESULTS: Compared with the solo hUC-MSC-grafted or curcumin groups, combined curcumin-hUC-MSC therapy significantly improved the functional performance outcomes, diminished the infarct volumes and the cerebral edema. The combined treatment promoted anti-inflammatory microglia polarization via Nrf2 pathway and decreased the expression of ROS, oxidative mediators and pro-inflammatory cytokines, while elevating the expression of the anti-inflammatory cytokines. Nrf2 knockout abolished the antioxidant stress and anti-inflammation effects mediated with combined treatment. Moreover, the combined treatment enhanced the phosphorylation of AKT and GSK3ß, inhibited the ß-TrCP nucleus translocation, accompanied with Nrf2 activation in the nucleus. AKT inhibitor MK2206 activated GSK3ß and ß-TrCP and suppressed Nrf2 phosphorylation in nucleus, whereas MK2206 with the GSK3ß inhibitor TDZD-8 reversed these phenomena. Furthermore, combined treatment followed by GSK3ß inhibition with TDZD-8 restricted ß-TrCP nucleus accumulation, which facilitated Nrf2 expression. CONCLUSIONS: We have demonstrated that combined curcumin-hUC-MSC therapy exerts anti-inflammation and antioxidant stress efficacy mediated by anti-inflammatory microglia polarization via AKT/GSK-3ß/ß-TrCP/Nrf2 axis and an improved neurological function after AIS.

A protein sequence-based deep transfer learning framework for identifying human proteome-wide deubiquitinase-substrate interactions.

Protein ubiquitination regulates a wide range of cellular processes. The degree of protein ubiquitination is determined by the delicate balance between ubiquitin ligase (E3)-mediated ubiquitination and deubiquitinase (DUB)-mediated deubiquitination. In comparison to the E3-substrate interactions, the DUB-substrate interactions (DSIs) remain insufficiently investigated. To address this challenge, we introduce a protein sequence-based ab initio method, TransDSI, which transfers proteome-scale evolutionary information to predict unknown DSIs despite inadequate training datasets. An explainable module is integrated to suggest the critical protein regions for DSIs while predicting DSIs. TransDSI outperforms multiple machine learning strategies against both cross-validation and independent test. Two predicted DUBs (USP11 and USP20) for FOXP3 are validated by "wet lab" experiments, along with two predicted substrates (AR and p53) for USP22. TransDSI provides new functional perspective on proteins by identifying regulatory DSIs, and offers clues for potential tumor drug target discovery and precision drug application.

Small molecule-nanobody conjugate induced proximity controls intracellular processes and modulates endogenous unligandable targets.

Chemically induced proximity (CIP) is a powerful tool to study cellular functions. However with current CIP inducers it is difficult to directly modulate unligandable and endogenous targets, and therapeutic translational potential is also restricted. Herein, we combine CIP and chemical nanobody engineering and create cell-permeable small molecule-nanobody conjugate inducers of proximity (SNACIPs). The SNACIP inducer cRGT carrying a cyclic cell-penetrating peptide rapidly enters live cells and dimerizes eDHFR and GFP-variants. cRGT enables minute-scale, reversible, no-wash and dose-dependent control of cellular processes including signaling cascade, cargo transport and ferroptosis. Small-molecule motifs can also be installed via post-translational modifications. Therefore, latent-type SNACIPs including cRTC are designed that are functionally assembled inside living cells. cRTC contains a nanobody against an intrinsically disordered protein TPX2, a microtubule nucleation factor overexpressed in various cancers. Cancer cell proliferation is inhibited and tumor growth is suppressed in vivo. Hence, SNACIPs are valuable proximity inducers for regulating cellular functions.

Red-Light-Activatable AND-Gated Antitumor Immunosuppressant.

Immunosuppressants are emerging as promising candidates for cancer therapy with lower cytotoxicity compared to traditional chemotherapy drugs; yet, the intrinsic side effects such as immunosuppression remain a critical concern. Herein, we introduce a photoactivatable antitumor immunosuppressant called dmBODIPY-FTY720 (BF) that shows no cytotoxicity but can be temporally and locally activated by deep-red light illumination to induce tumor cell apoptosis. To further reduce potential side effects, we integrate BF with another classic photosensitizer called methylene blue (MB) that is activated under the same wavelength of deep-red light (>650 nm) and successfully establish a red-light-activatable AND Boolean logic gate through a mechanism that we found to be synergetic apoptotic induction. At further decreased dosages, deep-red light illumination does not induce cell death in the presence of either BF or MB, but significant cancer cell death is triggered in the presence of both drugs. Therefore, the dosage of BF is further reduced, which will be highly beneficial to minimize any potential side effects of BF. This AND-gated strategy has been successfully applied in vivo for effective suppression of hepatocarcinoma tumors in living mice.

Integrated platform for proteome profiling with combination of microreversed phase based protein and peptide separation via online solvent exchange and protein digestion.

An online integrated platform for proteome profiling was established, with the combination of protein separation by microreversed phase liquid chromatography (µRPLC), online acetonitrile (ACN) removal, and pH adjustment by a hollow fiber membrane interface (HFMI), online digestion by an immobilized enzymatic microreactor (IMER), as well as peptide separation and proteins identification by µRPLC or nano-RPLC-electrospray ionization tandem mass spectrometry (µRPLC-ESI-MS/MS). To evaluate the performance of such a platform, a three-protein mixture with mass ranging from 5 to 500 ng was analyzed automatically. Compared to the offline counterpart, although similar protein sequence coverages were obtained by the integrated platform, the signal intensity of total ion chromatogram was improved by almost 4 times. In addition, such an integrated platform was further applied for the analysis of extracted proteins from rat brain. Compared to the results obtained by offline counterpart and traditional MudPIT approach under similar conditions, by the integrated platform, the identified protein group number was comparable, but the analysis time was shortened to less than half of that taken by the traditional approaches. All these results demonstrated that our developed integrated platform might offer a promising tool for high-throughput and large-scale profiling of proteomes.

Nano-flow multidimensional liquid chromatography platform integrated with combination of protein and peptide separation for proteome analysis.

An integrated multidimensional nano-flow liquid chromatography platform with the combination of protein and peptide separation via online digestion by an immobilized enzymatic reactor was established, and successfully applied for proteome analysis. By this platform, proteins were first separated by a weak anion and weak cation mixed-bed microcolumn under a series of salt steps, online digested by a trypsin immobilized enzymatic reactor, digests trapped and desalted by a C18 precolumn, separated by nano-reversed phase liquid chromatography, and finally identified by electrospray ionization-MS/MS. To evaluate the performance of such a platform, Escherichia coli whole cell lysate proteins were analyzed. Compared with the results obtained by shotgun approach, the identified protein number was increased by 6%, with the consumed time decreased from 38 to 14 h. We also compared with integrate platform based on micro-HPLC, and the required sample amount was decreased to 8 µg. These results demonstrated that such an integrated approach would be an attractive alternative to commonly applied approaches for proteome research.

Sensitive methods for detection of SARS-CoV-2 RNA.

The occurrence of the COVID-19 pandemic caused by the SARS-CoV-2 virus since the end of 2019 has significantly affected the entire world. Now SARS-CoV-2 diagnostic tests are not only required for screening of suspected infected people for their medical treatment, but have also become a routine diagnosis for all people at a place where new cases have emerged in order to control spread of the disease from that region. For these reasons, sensitive methods for detection of SARS-CoV-2 are highly needed in order to avoid undetected infections. In addition, sample pooling that uses pooled specimens has been routinely employed as a time- and cost-effective strategy for community monitoring of SARS-CoV-2. In this regard, the content of each viral RNA sample of an individual will be further diluted in detection; therefore, higher detection sensitivity would be rather preferred. Among nucleic acid-based detection methods, isothermal nucleic acid amplifications are considered quite promising because they typically take less time to complete the test (even less than 20 min) without the need of thermal cycles. Hence, it does not necessitate the use of highly costly real-time PCR machines. According to recently published isothermal nucleic acid amplification methods, the reverse transcription recombinase polymerase amplification (RT-RPA) approach shows outstanding sensitivity with up to single-copy sensitivity in a test reaction. This chapter will mainly focus on how to employ RT-RPA technology to sensitively detect SARS-CoV-2 RNA. Besides, recently published RT-RPA based detection methods will be summarized and compared regarding their detection parameters and the primers and probes being used. In addition, we will also highlight the key considerations on how to design an ultrasensitive RT-RPA assay and the precautions needed to conduct the assay. Moreover, based on our recent report, we will also detail the methods we developed to detect SARS-CoV-2 RNA using modified RT-RPA, or RT-ERA, with single-copy sensitivity and the possible extensions beyond this method.

Adenosine A2A Receptor Suppressed Astrocyte-Mediated Inflammation Through the Inhibition of STAT3/YKL-40 Axis in Mice With Chronic Cerebral Hypoperfusion-induced White Matter Lesions.

White matter lesions are an important pathological manifestation of cerebral small vessel disease, with inflammation playing a pivotal role in their development. The adenosine A2a receptor (ADORA2A) is known to inhibit the inflammation mediated by microglia, but its effect on astrocytes is unknown. Additionally, although the level of YKL-40 (expressed mainly in astrocytes) has been shown to be elevated in the model of white matter lesions induced by chronic cerebral hypoperfusion, the specific regulatory mechanism involved is not clear. In this study, we established in vivo and in vitro chronic cerebral hypoperfusion models to explore whether the ADORA2A regulated astrocyte-mediated inflammation through STAT3/YKL-40 axis and using immunohistochemical, western blotting, ELISA, PCR, and other techniques to verify the effect of astrocytes ADORA2A on the white matter injury. The in vivo experiments showed that activation of the ADORA2A decreased the expression of both STAT3 and YKL-40 in the astrocytes and alleviated the white matter injury, whereas its inhibition had the opposite effects. Similarly, ADORA2A inhibition significantly increased the expression of STAT3 and YKL-40 in astrocytes in vitro, with more proinflammatory cytokines being released by astrocytes. STAT3 inhibition enhanced the inhibitory effect of ADORA2A on YKL-40 synthesis, whereas its activation reversed the phenomenon. These results suggest that the activation of ADORA2A in astrocytes can inhibit the inflammation mediated by the STAT3/YKL-40 axis and thereby reduce white matter injury in cerebral small vessel disease.

Corrigendum: Adenosine A2A Receptor Suppressed Astrocyte-Mediated Inflammation through the Inhibition of STAT3/YKL-40 Axis in Mice with Chronic Cerebral Hypoperfusion-Induced White Matter Lesions.

[This corrects the article DOI: 10.3389/fimmu.2022.841290.].

Integration of Human Protein Sequence and Protein-Protein Interaction Data by Graph Autoencoder to Identify Novel Protein-Abnormal Phenotype Associations.

Understanding gene functions and their associated abnormal phenotypes is crucial in the prevention, diagnosis and treatment against diseases. The Human Phenotype Ontology (HPO) is a standardized vocabulary for describing the phenotype abnormalities associated with human diseases. However, the current HPO annotations are far from completion, and only a small fraction of human protein-coding genes has HPO annotations. Thus, it is necessary to predict protein-phenotype associations using computational methods. Protein sequences can indicate the structure and function of the proteins, and interacting proteins are more likely to have same function. It is promising to integrate these features for predicting HPO annotations of human protein. We developed GraphPheno, a semi-supervised method based on graph autoencoders, which does not require feature engineering to capture deep features from protein sequences, while also taking into account the topological properties in the protein-protein interaction network to predict the relationships between human genes/proteins and abnormal phenotypes. Cross validation and independent dataset tests show that GraphPheno has satisfactory prediction performance. The algorithm is further confirmed on automatic HPO annotation for no-knowledge proteins under the benchmark of the second Critical Assessment of Functional Annotation, 2013-2014 (CAFA2), where GraphPheno surpasses most existing methods. Further bioinformatics analysis shows that predicted certain phenotype-associated genes using GraphPheno share similar biological properties with known ones. In a case study on the phenotype of abnormality of mitochondrial respiratory chain, top prioritized genes are validated by recent papers. We believe that GraphPheno will help to reveal more associations between genes and phenotypes, and contribute to the discovery of drug targets.

Structural and functional insights into a novel pre-clinical-stage antibody targeting IL-17A for treatment of autoimmune diseases.

The pro-inflammatory cytokine interleukin-17A (IL-17A) is a key driver of multiple inflammatory and immune disorders. Therapeutic antibodies targeting IL-17A have been proven effective in treating patients with these diseases; however, large variations in clinical outcomes have been observed with different antibodies. In this study, we developed HB0017, a novel monoclonal antibody that targets human IL-17A. HB0017 specifically and strongly bound to human, cynomolgus monkey, and mouse IL-17A at the physiological interface with the IL-17A receptor. In human and monkey cells, HB0017 potently antagonized the functions of IL-17A through competitive binding. HB0017 functioned equivalently to that of clinically approved antibodies in terms of therapeutic efficacy for inflammatory disorders and psoriasis in a mouse model. The results indicate that HB0017 may be an alternative biological therapy for treating patients with inflammation and autoimmune diseases.

Integrated sample pretreatment system for N-linked glycosylation site profiling with combination of hydrophilic interaction chromatography and PNGase F immobilized enzymatic reactor via a strong cation exchange precolumn.

An integrated sample pretreatment system, composed of a click maltose hydrophilic interaction chromatography (HILIC) column, a strong cation exchange (SCX) precolumn, and a PNGase F immobilized enzymatic reactor (IMER), was established for the simultaneous glycopeptide enrichment, sample buffer exchange, and online deglycosylation, by which the sample pretreatment for glycoproteome could be performed online automatically, beneficial to improve the efficiency and sensitivity of the N-linked glycosylation site identification. With such a system, the deglycosylated glycopeptide from the digests of avidin with the coexistence of 50 times (mass ratio) BSA could be selectively detected, and the detection limit as low as 5 fmol was achieved. Moreover, the sample pretreatment time was significantly shortened to ~1 h. Such a system was further successfully applied for analyzing the digest of the soluble fraction extracted from rat brain. A total of 120 unique glycoprotein groups and 196 N-linked glycosylation sites were identified by nanoreversed phase liquid chromatography-electrospray ionization-tandem mass spectrometry (nanoRPLC-ESI-MS/MS), with the injected digests amount as 6 µg. All these results demonstrate that the integrated system is of great promise for N-linked glycosylation site profiling and could be further online coupled with nanoHPLC-ESI-MS/MS to achieve high-throughput glycoproteome analysis.

Chromatin-associated SUMOylation controls the transcriptional switch between plant development and heat stress responses.

The post-translational protein modification known as SUMOylation has conserved roles in the heat stress responses of various species. The functional connection between the global regulation of gene expression and chromatin-associated SUMOylation in plant cells is unknown. Here, we uncovered a genome-wide relationship between chromatin-associated SUMOylation and transcriptional switches in Arabidopsis thaliana grown at room temperature, exposed to heat stress, and exposed to heat stress followed by recovery. The small ubiquitin-like modifier (SUMO)-associated chromatin sites, characterized by whole-genome ChIP-seq, were generally associated with active chromatin markers. In response to heat stress, chromatin-associated SUMO signals increased at promoter-transcriptional start site regions and decreased in gene bodies. RNA-seq analysis supported the role of chromatin-associated SUMOylation in transcriptional activation during rapid responses to high temperature. Changes in SUMO signals on chromatin were associated with the upregulation of heat-responsive genes and the downregulation of growth-related genes. Disruption of the SUMO ligase gene SIZ1 abolished SUMO signals on chromatin and attenuated rapid transcriptional responses to heat stress. The SUMO signal peaks were enriched in DNA elements recognized by distinct groups of transcription factors under different temperature conditions. These observations provide evidence that chromatin-associated SUMOylation regulates the transcriptional switch between development and heat stress response in plant cells.

A Novel Bispecific Antibody Targeting PD-L1 and VEGF With Combined Anti-Tumor Activities.

Therapeutic monoclonal antibodies (mAbs) blocking immune checkpoints have been mainly used as monotherapy. Recently, combination therapy targeting multiple immune checkpoints has recently been explored to increase anti-cancer efficacy. Particularly, a single molecule targeting more than one checkpoints has been investigated. As dual blocking of PD-1/PD-L1 and VEGF/VEGFR has demonstrated synergism in anti-tumor activities, we developed a novel bispecific antibody, termed HB0025, which is formed via fusing the domain 2 of vascular endothelial growth factor receptor 1 (VEGFR1D2) and anti-PD-L1 mAb by using mAb-Trap technology. HB0025 almost completely retains the binding affinities and the biological activities in-vitro when compared with the parent anti-PD-L1 mAb or VEGFR1D2 fusion protein. Preclinical data demonstrated that HB0025 was more effective in inhibiting cancer growth than anti PD-L1 mAb or VEGFR1D2 fusion protein. Thus, our bispecific antibody may bring about greater clinical benefits and broader indications.

Prokaryotic expression, purification and characterization of human cyclooxygenase-2.

Cyclooxygenase-2 (COX-2) is a key enzyme which catalyzes the conversion of arachidonic acid (AA) into prostaglandins (PGs). It plays an important role in pathophysiological processes, such as tumorigenesis, angiogenesis, inflammation and tumor cell drug resistance. Therefore, COX-2 has been viewed as an important target for cancer therapy. The preparation of COX-2 protein is an important initial step for the subsequent development of COX-2 inhibitors. In this study, we report a strategy to heterologously express truncated human COX-2 (trCOX-2) in Escherichia coli (E. coli) BL21(DE3) host cells. Following denaturation, purification and renaturation, we successfully obtained enzymatically active trCOX-2 containing 257 residues of the C-terminus. Homology modeling and molecular docking analyses revealed that trCOX-2 retained the predicted 3D catalytic domain structure and AA could still bind to its hydrophobic groove. Western blot analysis and ELISA indicated that the trCOX-2 still retained its characteristic antigenicity and binding activity, while COX assays revealed that trCOX-2 maintained its enzyme activity. On the whole, in this study, we provided a novel method to isolate trCOX-2 possessing AA binding and catalytic activities. This study thus lays a foundation to facilitate further investigations of COX-2 and offers a valuable method with which to achieve the prokaryotic expression of a eukaryotic membrane protein.

Integrated SDS removal and protein digestion by hollow fiber membrane based device for SDS-assisted proteome analysis.

In this work, a novel integrated sample preparation device for SDS-assisted proteome analysis was developed, by which proteins dissolved in 4% (w/v) SDS were first diluted by 50% methanol, and then SDS was online removed by a hollow fiber membrane interface (HFMI) with 50mM ammonium bicarbonate (pH 8.0) as an exchange buffer, finally digested by an immobilized enzyme reactor (IMER). To evaluate the performance of such an integrated device, bovine serum albumin dissolved in 4% (w/v) SDS as a model sample was analyzed; it could be found that similar to that obtained by direct analysis of BSA digests without SDS (the sequence coverage of 60.3±1.0%, n=3), with HFMI as an interface for SDS removal, BSA was identified with the sequence coverage of 61.0±1.0% (n=3). However, without SDS removal by HFMI, BSA could not be digested by the IMER and none peptides could be detected. In addition, such an integrated sample preparation device was also applied for the analysis of SDS extracted proteins from rat brain, compared to those obtained by filter-aided sample preparation (FASP), not only the identified protein group and unique peptide number were increased by 12% and 39% respectively, but also the sample pretreatment time was shortened from 24h to 4h. All these results demonstrated that such an integrated sample preparation device would provide an alternative tool for SDS assisted proteome analysis.