Using ATCLSTM-Kcr to predict and generate the human lysine crotonylation database.

Lysine crotonylation (Kcr) is an evolutionarily conserved protein post-translational modifications, which plays an important role in cellular physiology and pathology, such as chromatin remodeling, gene transcription regulation, telomere maintenance, inflammation, and cancer. Tandem mass spectrometry (LC-MS/MS) has been used to identify the global Kcr profiling of human, at the same time, many computing methods have been developed to predict Kcr sites without high experiment cost. Deep learning network solves the problem of manual feature design and selection in traditional machine learning (NLP), especially the algorithms in natural language processing which treated peptides as sentences, thus can extract more in-depth information and obtain higher accuracy.

Spatial region-resolved proteome map reveals mechanism of COVID-19-associated heart injury.

Direct myocardial and vascular injuries due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-driven inflammation is the leading cause of acute cardiac injury associated with coronavirus disease 2019 (COVID-19). However, in-depth knowledge of the injury characteristics of the heart affected by inflammation is lacking. In this study, using a quantitative spatial proteomics strategy that combines comparative anatomy, laser-capture microdissection, and histological examination, we establish a region-resolved proteome map of the myocardia and microvessels with obvious inflammatory cells from hearts of patients with COVID-19.

Global profiling of lysine succinylation in human lungs.

The lysine succinylation (Ksucc) is involved in many core energy metabolism pathways and affects the metabolic process in mitochondria, making this modification highly valuable for studying diseases related to mitochondrial disorders. In this paper, we used liquid chromatography with tandem mass spectrometry (LC-MS/MS) to perform the first global profiling of succinylation in human lungs under normal physiological conditions. Using an MS-based platform, we identified 1485 Ksucc sites in 568 proteins.

Mutations Contribute to Acquired Cetuximab Resistance in Patients with Metastatic Colorectal Cancer.

Mutations in are considered to be the main drivers of acquired resistance to epidermal growth factor receptor (EGFR) blockade in patients with metastatic colorectal cancer (mCRC). However, the potential role of other genes downstream of the EGFR signaling pathway in conferring acquired resistance has not been extensively investigated. Using circulating tumor DNA (ctDNA) from patients with mCRC and with acquired cetuximab resistance, we developed a targeted amplicon ultra-deep sequencing method to screen for low-abundance somatic mutations in a panel of genes that encode components of the EGFR signaling pathway.

Using the entrapment sequence method as a standard to evaluate key steps of proteomics data analysis process.

Background: The mass spectrometry based technical pipeline has provided a high-throughput, high-sensitivity and high-resolution platform for post-genomic biology. Varied models and algorithms are implemented by different tools to improve proteomics data analysis. The target-decoy searching strategy has become the most popular strategy to control false identification in peptide and protein identifications.

Identification of novel serological tumor markers for human prostate cancer using integrative transcriptome and proteome analysis.

The aim of this study was to identify novel serological tumor markers for human prostate cancer (PCa). We compared the gene expression profile of PCa tissues to adjacent benign tissues of prostate using gene expression microarray. 1207 genes that were consistently different from adjacent benign tissues of prostate (paired t test, P<0.

An overview of human protein databases and their application to functional proteomics in health and disease.

Functional proteomics can be defined as a strategy to couple proteomic information with biochemical and physiological analyses with the aim of understanding better the functions of proteins in normal and diseased organs. In recent years, a variety of publicly available bioinformatics databases have been developed to support protein-related information management and biological knowledge discovery. In addition to being used to annotate the proteome, these resources also offer the opportunity to develop global approaches to the study of the functional role of proteins both in health and disease.

[Identification, modeling and simulation of key pathways underlying certain cancers].

Cancer is a complex disease which greatly affects the human health. It has been widely reported that certain biological pathways play important roles in the process of tumorigenesis, tumor progression and metastasis. Identification and simulation of these pathways can help to understand the underlying mechanisms.

Purification and identification of 1-deoxynojirimycin (DNJ) in okara fermented by Bacillus subtilis B2 from Chinese traditional food (Meitaoza).

This study was to purify an alpha-glucosidase inhibitor from okara (soy pulp) fermented by Bacillus subtilis B2 and to identify its chemical structure. Membrane dialysis, active charcoal, CM-Sepharose chromatography, and preparative thin-layer chromatography (TLC) were used in the purification, while positive mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectrometry were used in the identification. The MS and NMR data showed that the purified alpha-glucosidase inhibitor was 1-deoxynojirimycin (DNJ) with a molecular weight of 163 Da.

[Advances on bioinformatic research in transcription factor binding sites].

Transcription regulation is carried out by the interactions between transcription factors and their binding sites in DNA. Transcription factor binding sites (TFBS) are short, degenerate nucleotide sequences, and usually are 6-20 bp long. Accurate prediction of TFBSs is a crucial step towards understanding the regulation mechanism of transcription and constructing transcriptional regulatory networks.

Effects of sources of carbon and nitrogen on production of α-glucosidase inhibitor by a newly isolated strain of Bacillus subtilis B2.

This study examined production of α-glucosidase inhibitors by Bacillus subtilis B2 in Luria-Bertani (LB) fermentation with okara, soy powder, starch or pectin as additional source of carbon and nitrogen. All the fermentation broths of B. subtilis B2 exhibited gradual increase in α-glucosidase inhibitory activity during the fermentation process with or without supplemented source of carbon or nitrogen.

[Research on modular organization of gene regulatory network].

Gene regulatory network is very important for researchers to understand biological processes and gene functions. It can deliver complex information about how could large amount of genes be regulated by transcriptional factors and translated into proteins which can carried out biological functions. Generally, knowledge of network topological structure and organization formation can be used to find the regulatory mechanism of genes in the regulatory network.

[Constructing gene regulatory network from microarray data].

With the rapid deposition of the microarray data in recent years, microarray data has increasingly become an important data source for bioinformatics research. Based on microarray date, constructing gene regulatory networks has also become a hotspot. By constructing the gene regulatory network, we can identify the complicated regulatory relationships, uncover the regulatory patterns in the cell, and gain the systematic view for biological process.

[The analysis method and progress in the study of codon bias].

Codon bias refers to the nonrandom usage of synonymous codons for encoding amino acids in organisms. As it is related to the carrier molecular of genetic information (DNA) and functional molecular (protein) of life, this phenomenon implicates important biological sense. In this review, we summarize the basic theories and analysis methods about codon bias; and present the softwares and websites which are usually used for codon usage analysis.

Network analysis of the protein chain tertiary structures of heterocomplexes.

In this paper, the tertiary structures of protein chains of heterocomplexes were mapped to 2D networks; based on the mapping approach, statistical properties of these networks were systematically studied. Firstly, our experimental results confirmed that the networks derived from protein structures possess small-world properties. Secondly, an interesting relationship between network average degree and the network size was discovered, which was quantified as an empirical function enabling us to estimate the number of residue contacts of the protein chains accurately.

Prediction of protein secondary structure using improved two-level neural network architecture.

In this paper we propose constructing an improved two-level neural network to predict protein secondary structure. Firstly, we code the whole protein composition information as the inputs to the first-level network besides the evolutionary information. Secondly, we calculate the reliability score for each residue position based on the output of the first-level network, and the role of the second-level network is to take full advantage of the residues with a higher reliability score to impact the neighboring residues with a lower one for improving the whole prediction accuracy.

[Strategy for the protein identification of human proteome expression profile: selection of searching database].

Widely used method of protein identification for high-throughout proteome expression profile studies was database-dependent, so the selection of databases for the protein identification was very important. Despite the deficiency of available human protein databases, the complementarity of human proteins could be got mainly from human genome but not from the protein databases of other organisms. According to the comparison of the current protein databases from different aspects, IPI was recommended for the basic identification for the studies of human proteome expression profile, and other human protein or nucleic acid databases were needed for the complementary identification and novel protein mining.

[The genome comparison of SARS-CoV and other coronaviruses].

The genome comparison of inter-species and intra-species can give us much information about the origin and evolution of viruses. There are 137 mutation sites in the 17 genomes of SARS-CoV,and the mutation rate is about 8.04 x 10(-3) substitution/site/year.

[Gene prediction and function research of SARS-CoV(BJ01)].

Through reading the articles, this study points out the shortage of gene prediction and function research about SARS-CoV, and predict it again for developing effective drugs and future vaccines. Using twelve gene prediction methods to predict coronavirus known genes, we select four better methods including Heuristic models, Gene Identification, ZCURVE_CoV and ORF FINDER to predict SARS-CoV(BJ01), and use ATGpr for analyzing probability of initiation codon and Kozak rule, search transcription regulating sequence(TRS) in order to improve the accuracy of predicted genes. Twenty-one probable new genes with more than 50 amino acids have been obtained excluding 13 ORFs which are similar to the genes of NCBI and relative articles.

[Transcriptional regulation of gamma- and epsilon-globin genes by basic Krüppel-like factor].

To study the transcription regulatory function of basic Krüppel-like factor (BKLF)on gamma- and epsilon-globin genes, recombinant expression vectors containing the full-length human BKLF gene, and a deletion mutant that lost N-terminal 40 amino acids, were constructed and used, respectively, to transiently transfect COS7 cells in order to assay their reporter activities. Results showed that hBKLF was able to repress the activity of gamma- and epsilon-globin gene promoters, while the antisense nucleic acid specific for hBKLF activated the transcription of these promoters. Deleting 40 amino acids from N-terminus did not influence the transcriptional repression of hBKLF.

[Subcellular localization of basic Krüppel-like factor].

To understand the function of basic Krüppel-like factor (BKLF), it was confirmed by direct fluorescence and indirect fluorescence observation that hBKLF was localized in nucleus, and distributed throughout nucleoplasm in a speckled pattern, except the nucleoli. This pattern is similar to many but not all transcription factors. To clarify the specific sequence responsible for its nuclear localization, a series of deletion mutants of GFP/hBKLF were constructed.