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. In this work, we establish a Kcr prediction model named ATCLSTM-Kcr which use self-attention mechanism combined with NLP method to highlight the important features and further capture the internal correlation of the features, to realize the feature enhancement and noise reduction modules of the model. Independent tests have proved that ATCLSTM-Kcr has better accuracy and robustness than similar prediction tools. Then, we design pipeline to generate MS-based benchmark dataset to avoid the false negatives caused by MS-detectability and improve the sensitivity of Kcr prediction. Finally, we develop a Human Lysine Crotonylation Database (HLCD) which using ATCLSTM-Kcr and the two representative deep learning models to score all lysine sites of human proteome, and annotate all Kcr sites identified by MS of current published literatures. HLCD provides an integrated platform for human Kcr sites prediction and screening through multiple prediction scores and conditions, and can be accessed on the website:www.urimarker.com/HLCD/. SIGNIFICANCE: Lysine crotonylation (Kcr) plays an important role in cellular physiology and pathology, such as chromatin remodeling, gene transcription regulation and cancer. To better elucidate the molecular mechanisms of crotonylation and reduce the high experimental cost, we establish a deep learning Kcr prediction model and solve the problem of false negatives caused by the detectability of mass spectrometry (MS). Finally, we develop a Human Lysine Crotonylation Database to score all lysine sites of human proteome, and annotate all Kcr sites identified by MS of current published literatures. Our work provides a convenient platform for human Kcr sites prediction and screening through multiple prediction scores and conditions.

Proteomic and phosphoproteomic characteristics of the cortex, hippocampus, thalamus, lung, and kidney in COVID-19-infected female K18-hACE2 mice.

BACKGROUND: Neurological damage caused by coronavirus disease 2019 (COVID-19) has attracted increasing attention. Recently, through autopsies of patients with COVID-19, the direct identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in their central nervous system (CNS) has been reported, indicating that SARS-CoV-2 might directly attack the CNS. The need to prevent COVID-19-induced severe injuries and potential sequelae is urgent, requiring the elucidation of large-scale molecular mechanisms in vivo. METHODS: In this study, we performed liquid chromatography-mass spectrometry-based proteomic and phosphoproteomic analyses of the cortex, hippocampus, thalamus, lungs, and kidneys of SARS-CoV-2-infected K18-hACE2 female mice. We then performed comprehensive bioinformatic analyses, including differential analyses, functional enrichment, and kinase prediction, to identify key molecules involved in COVID-19. FINDINGS: We found that the cortex had higher viral loads than did the lungs, and the kidneys did not have SARS-COV-2. After SARS-CoV-2 infection, RIG-I-associated virus recognition, antigen processing and presentation, and complement and coagulation cascades were activated to different degrees in all five organs, especially the lungs. The infected cortex exhibited disorders of multiple organelles and biological processes, including dysregulated spliceosome, ribosome, peroxisome, proteasome, endosome, and mitochondrial oxidative respiratory chain. The hippocampus and thalamus had fewer disorders than did the cortex; however, hyperphosphorylation of Mapt/Tau, which may contribute to neurodegenerative diseases, such as Alzheimer's disease, was found in all three brain regions. Moreover, SARS-CoV-2-induced elevation of human angiotensin-converting enzyme 2 (hACE2) was observed in the lungs and kidneys, but not in the three brain regions. Although the virus was not detected, the kidneys expressed high levels of hACE2 and exhibited obvious functional dysregulation after infection. This indicates that SARS-CoV-2 can cause tissue infections or damage via complicated routes. Thus, the treatment of COVID-19 requires a multipronged approach. INTERPRETATION: This study provides observations and in vivo datasets for COVID-19-associated proteomic and phosphoproteomic alterations in multiple organs, especially cerebral tissues, of K18-hACE2 mice. In mature drug databases, the differentially expressed proteins and predicted kinases in this study can be used as baits to identify candidate therapeutic drugs for COVID-19. This study can serve as a solid resource for the scientific community. The data in this manuscript will serve as a starting point for future research on COVID-19-associated encephalopathy. FUNDING: This study was supported by grants from the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences, the National Natural Science Foundation of China, and the Natural Science Foundation of Beijing.

Phosphoproteome profiling of mouse liver during normal aging.

BACKGROUND: Aging is a complex biological process accompanied by a time-dependent functional decline that affects most living organisms. Omics studies help to comprehensively understand the mechanism of aging and discover potential intervention methods. Old mice are frequently obese with a fatty liver. METHODS: We applied mass spectrometry-based phosphoproteomics to obtain a global phosphorylation profile of the liver in mice aged 2 or 18 months. MaxQuant was used for quantitative analysis and PCA was used for unsupervised clustering. RESULTS: Through phosphoproteome analysis, a total of 5,685 phosphosites in 2,335 proteins were filtered for quantitative analysis. PCA analysis of both the phosphoproteome and transcriptome data could distinguish young and old mice. However, from kinase prediction, kinase-substrate interaction analysis, and KEGG functional enrichment analysis done with phosphoproteome data, we observed high phosphorylation of fatty acid biosynthesis, ß-oxidation, and potential secretory processes, together with low phosphorylation of the Egfr-Sos1-Araf/Braf-Map2k1-Mapk1 pathway and Ctnnb1 during aging. Proteins with differentially expressed phosphosites seemed more directly related to the aging-associated fatty liver phenotype than the differentially expressed transcripts. The phosphoproteome may reveal distinctive biological functions that are lost in the transcriptome. CONCLUSIONS: In summary, we constructed a phosphorylation-associated network in the mouse liver during normal aging, which may help to discover novel antiaging strategies.

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. We then compared these sites with those previously identified in human succinylome studies to investigate specific succinylated proteins and identify their possible functions in the lung and to explore the substrate preferences of succinylation modifiers in different cell lines and at different subcellular localizations. Our work expands the succinylation database and supplementary materials on the human succinylome and will thus help in further study of the function of Ksucc and regulation under related physiological and pathological conditions.

Global Lysine Crotonylation Profiling of Mouse Liver.

Lysine crotonylation (Kcr) is a recently discovered post-translational modification that potentially regulates multiple biological processes. With an objective to expand the available crotonylation datasets, LC-MS/MS is performed using mouse liver samples under normal physiological conditions to obtain in vivo crotonylome. A label-free strategy is used and 10 034 Class I (localization probabilities > 0.75) crotonylated sites are identified in 2245 proteins. The KcrE, KcrD, and EKcr motifs are significantly enriched in the crotonylated peptides. The identified crotonylated proteins are mostly enzymes and primarily located in the cytoplasm and nucleus. Functional enrichment analysis based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes shows that the crotonylated proteins are closely related to the purine-containing compound metabolic process, ribose phosphate metabolic process, carbon metabolism pathway, ribosome pathway, and a series of metabolism-associated biological processes. To the best of the authors' knowledge, this research provides the first report on the mouse liver crotonylome. Furthermore, it offers additional evidence that crotonylation exists in non-histone proteins, and is likely involved in various biological processes. The mass spectrometry proteomics data have been deposited in the ProteomeXchange Consortium with the dataset identifiers PXD019145.

[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. The related fields about codon bias and the research progress are also introduced.

[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.

[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. For predicted proteins, we use ProtParam to analyse physical and chemical features; SignalP to analyse signal peptide; BLAST, FASTA to search similar sequences; TMPred, TMHMM, PFAM and HMMTOP to analyse domain and motif in order to improve reliability of gene function prediction. At the same time, we separate the 21 ORFs into four classes using codition of four gene prediction methods, match score, match expection and match length between predicted gene and Coronavirus known gene. In the end, we discuss the results and analyse the reasons.

[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. The distribution of the segregating sites is not steady,the most variable region appears in S1 protein,and the nucleotide sequence of RNA-dependent RNA polymerase has very few mutation sites. The substitution bias of nucleotide acids and amino acids indicates the non-random drift products. The comparison of genome structures of SARS-CoV and other coronaviruses shows that SARS-CoV and IBV share the same genome structure. Phylogenetic analyses of conserved genes of coronaviruses indicate that SARS-CoV is a new branch of coronaviruses and appears more close to the group II coronaviruses. Interestingly,SARS-CoV shares some different features with different groups of coronaviruses. Additional analyses show that the first ORFs between S and E genes of some coronaviruses are transmembrane proteins and share the common motif,indicating the possible common ancestor. From the host distribution of different groups of coronaviruses and the phylogeny of s2m,we can deduce that avian is the probable natural host of SARS-CoV.

[Construction and application of an in silico elongation system of nucleic acid sequence].

Normally it is difficult to obtain full-length cDNA sequence of novel genes. More and more expressed sequence tags(ESTs) have been obtained since the start-up of human genome project. Powerful system is badly needed for data mining on these EST sequences. Based on a personal computer coupled with Linux operating system and EST database, the Blast software and Phrap software were used to construct a platform for in silico elongation of ESTs in our lab. The performance was tested using 11386 EST sequences and 511 partial-length cDNA sequences. Results demonstrated that 8373 EST and 389 cDNA sequence were elongated using this system. Thus the platform seems to be a fast way for full-length cDNA sequence cloning of new genes.