Proteomic analysis and prediction of amino acid variations that influence protein posttranslational modifications.

Accumulative studies have indicated that amino acid variations through changing the type of residues of the target sites or key flanking residues could directly or indirectly influence protein posttranslational modifications (PTMs) and bring about a detrimental effect on protein function. Computational mutation analysis can greatly narrow down the efforts on experimental work. To increase the utilization of current computational resources, we first provide an overview of computational prediction of amino acid variations that influence protein PTMs and their functional analysis. We also discuss the challenges that are faced while developing novel in silico approaches in the future. The development of better methods for mutation analysis-related protein PTMs will help to facilitate the development of personalized precision medicine.

Site-Specific Systematic Analysis of Lysine Modification Crosstalk.

Research has revealed that post-translational modifications (PTMs) that occur at lysine (PLMs) can cooperatively regulate various biological processes by crosstalk. However, the trend of the crosstalk between multiple PLMs and the properties of PLM crosstalk require additional investigation. Here, the crosstalk among acetylation, succinylation, and SUMOylation is systematically studied in a site-specific waz. First, crosstalk between SUMOylation is detected and succinylation is found to be underexpressed, whereas succinylation tends to crosstalk with acetylation and SUMOylation on the same lysine residue while PLM crosstalk is tissue-specific across different species. Further analysis reveals that different PLMs tend to occur crosstalk at diverse subcellular compartments and structural regions, and they participate in distinct biological processes and functions. Additionally, short-term evolutionary analysis shows that there is no additional evolutionary pressure on PLMs crosstalk sites, as found by comparison with singly modified sites. Finally, phylogenetic classification reveals that genes with co-occupied lysine crosstalk are more likely to have higher evolutionary similarity and possess a tendency to cluster in the specific branch. The integrated approach reported here has the potential for large-scale prioritization of in situ crosstalk of PLM candidates and provides a profound understanding of the underlying relationship between different lysine modifications.

Flexible and Fast Mapping of Peptides to a Proteome with ProteoMapper.

Bottom-up proteomics relies on the proteolytic or chemical cleavage of proteins into peptides, the identification of those peptides via mass spectrometry, and the mapping of the identified peptides back to the reference proteome to infer which possible proteins are identified. Reliable mapping of peptides to proteins still poses substantial challenges when considering similar proteins, protein families, splice isoforms, sequence variation, and possible residue mass modifications, combined with an imperfect and incomplete understanding of the proteome. The ProteoMapper tool enables a comprehensive and rapid mapping of peptides to a reference proteome. The indexer component creates a segmented index for an input proteome from a FASTA or PEFF file. The ProMaST component provides ultrafast mapping of one or more input peptides against the index. ProteoMapper allows searches that take into account known sequence variation encoded in PEFF files. It also enables fuzzy searches to find highly similar peptides with residue order changes or other isobaric or near-isobaric substitutions within a specified mass tolerance. We demonstrate an example of a one-hit-wonder identification in PeptideAtlas that may be better explained by a combination of catalogued and uncatalogued sequence variation in another highly observed protein. ProteoMapper is a free and open source, available for local use after downloading, embedding in other applications, as an online web tool at http://www.peptideatlas.org/map , and as a web service.

On human disease-causing amino acid variants: statistical study of sequence and structural patterns.

Statistical analysis was carried out on large set of naturally occurring human amino acid variations, and it was demonstrated that there is a preference for some amino acid substitutions to be associated with diseases. At an amino acid sequence level, it was shown that the disease-causing variants frequently involve drastic changes in amino acid physicochemical properties of proteins such as charge, hydrophobicity, and geometry. Structural analysis of variants involved in diseases and being frequently observed in human population showed similar trends: disease-causing variants tend to cause more changes in hydrogen bond network and salt bridges as compared with harmless amino acid mutations. Analysis of thermodynamics data reported in the literature, both experimental and computational, indicated that disease-causing variants tend to destabilize proteins and their interactions, which prompted us to investigate the effects of amino acid mutations on large databases of experimentally measured energy changes in unrelated proteins. Although the experimental datasets were linked neither to diseases nor exclusory to human proteins, the observed trends were the same: amino acid mutations tend to destabilize proteins and their interactions. Having in mind that structural and thermodynamics properties are interrelated, it is pointed out that any large change in any of them is anticipated to cause a disease.

Genomic Characterization and Molecular Evolution of Sapovirus in Children under 5 Years of Age.

Sapovirus (SaV) is a type of gastroenteric virus that can cause acute gastroenteritis. It is highly contagious, particularly among children under the age of 5. In this study, a total of 712 stool samples from children under the age of 5 with acute gastroenteritis were collected. Out of these samples, 28 tested positive for SaV, resulting in a detection rate of 3.93% (28/712). Samples with Ct < 30 were collected for library construction and high-throughput sequencing, resulting in the acquisition of nine complete genomes. According to Blast, eight of them were identified as GI.1, while the remaining one was GI.6. The GI.6 strain sequence reported in our study represents the first submission of the GI.6 strain complete genome sequence from mainland China to the Genbank database, thus filling the data gap in our country. Sequence identity analysis revealed significant nucleotide variations between the two genotypes of SaV and their corresponding prototype strains. Phylogenetic and genetic evolution analyses showed no evidence of recombination events in the obtained sequences. Population dynamics analysis demonstrated potential competitive inhibition between two lineages of GI.1. Our study provides insights into the molecular epidemiological and genetic evolution characteristics of SaV prevalent in the Nantong region of China, laying the foundation for disease prevention and control, as well as pathogen tracing related to SaV in this area.

Association between alleles, haplotypes, and amino acid variations in HLA class II genes and type 1 diabetes in Kuwaiti children.

Type 1 diabetes (T1D) is a complex autoimmune disorder that is highly prevalent globally. The interactions between genetic and environmental factors may trigger T1D in susceptible individuals. HLA genes play a significant role in T1D pathogenesis, and specific haplotypes are associated with an increased risk of developing the disease. Identifying risk haplotypes can greatly improve the genetic scoring for early diagnosis of T1D in difficult to rank subgroups. This study employed next-generation sequencing to evaluate the association between HLA class II alleles, haplotypes, and amino acids and T1D, by recruiting 95 children with T1D and 150 controls in the Kuwaiti population. Significant associations were identified for alleles at the HLA-DRB1, HLA-DQA1, and HLA-DQB1 loci, including DRB1*03:01:01, DQA1*05:01:01, and DQB1*02:01:01, which conferred high risk, and DRB1*11:04:01, DQA1*05:05:01, and DQB1*03:01:01, which were protective. The DRB1*03:01:01~DQA1*05:01:01~DQB1*02:01:01 haplotype was most strongly associated with the risk of developing T1D, while DRB1*11:04-DQA1*05:05-DQB1*03:01 was the only haplotype that rendered protection against T1D. We also identified 66 amino acid positions across the HLA-DRB1, HLA-DQA1, and HLA-DQB1 genes that were significantly associated with T1D, including novel associations. These results validate and extend our knowledge on the associations between HLA genes and T1D in Kuwaiti children. The identified risk alleles, haplotypes, and amino acid variations may influence disease development through effects on HLA structure and function and may allow early intervention via population-based screening efforts.

ASCARIS: Positional feature annotation and protein structure-based representation of single amino acid variations.

Background: Genomic variations may cause deleterious effects on protein functionality and perturb biological processes. Elucidating the effects of variations is critical for developing novel treatment strategies for diseases of genetic origin. Computational approaches have been aiding the work in this field by modeling and analyzing the mutational landscape. However, new approaches are required, especially for accurate representation and data-centric analysis of sequence variations. Method: In this study, we propose ASCARIS (Annotation and StruCture-bAsed RepresentatIon of Single amino acid variations), a method for the featurization (i.e., quantitative representation) of single amino acid variations (SAVs), which could be used for a variety of purposes, such as predicting their functional effects or building multi-omics-based integrative models. ASCARIS utilizes the direct and spatial correspondence between the location of the SAV on the sequence/structure and 30 different types of positional feature annotations (e.g., active/lipidation/glycosylation sites; calcium/metal/DNA binding, inter/transmembrane regions, etc.), along with structural features and physicochemical properties. The main novelty of this method lies in constructing reusable numerical representations of SAVs via functional annotations. Results: We statistically analyzed the relationship between these features and the consequences of variations and found that each carries information in this regard. To investigate potential applications of ASCARIS, we trained variant effect prediction models that utilize our SAV representations as input. We carried out an ablation study and a comparison against the state-of-the-art methods and observed that ASCARIS has a competing and complementary performance against widely-used predictors. ASCARIS can be used alone or in combination with other approaches to represent SAVs from a functional perspective. ASCARIS is available as a programmatic tool at https://github.com/HUBioDataLab/ASCARIS and as a web-service at https://huggingface.co/spaces/HUBioDataLab/ASCARIS.

Fluctuations in Metabolites and Bone Markers Across the Menstrual Cycle in Eumenorrheic Women and Oral Contraceptive Users.

CONTEXT: Little is known about changes in circulating metabolites during the menstrual cycle and how use of oral contraceptives (OCs) affects these changes. OBJECTIVES: To study fluctuations in circulating metabolite and bone marker levels during the menstrual/pill cycle in eumenorrheic women and OC users. METHODS: Plasma samples were collected from 28 eumenorrheic women and 10 OC users at 7 to 9 time points across a menstrual/pill cycle. Longitudinal and cross-sectional analyses were performed to examine the cycle- and OC-induced variations in the plasma metabolite and bone turnover marker levels. RESULTS: In eumenorrheic women, plasma levels of alanine, glutamine, threonine, and tyrosine varied significantly across the menstrual cycle, and all dropped to the lowest level around day 21 of the menstrual cycle. These amino acid concentrations were negatively correlated with fluctuations in progesterone and/or estrogen levels. A between-group analysis showed that plasma levels of alanine, glutamine, glycine, proline, and tyrosine were lower in OC users than in nonusers. Concomitantly, plasma C-terminal telopeptide of type I collagen (CTX) and N-terminal propeptide of type I procollagen (PINP) levels were lower in OC users. Intriguingly, when all data were pooled, variations in CTX and PINP levels were positively correlated with fluctuations in proline and glycine concentrations (r > 0.5 or 0.3 < r < 0.5, P < 0.05). CONCLUSIONS: The menstrual cycle and the use of OCs alter plasma levels of metabolites and bone turnover markers in young women. While the impact of these findings remains to be established, the lower glycine level among OC users and the accompanying lower CTX level supports that the use of OCs lowers collagen turnover in young women and may thereby have long-term implications for bone health among OC users.

Novel SFTSV Phylogeny Reveals New Reassortment Events and Migration Routes.

Severe fever with thrombocytopenia syndrome virus (SFTSV), the causative agent of a febrile human disease, was first identified from central and eastern provinces in China, and later in Japan and South Korea. Hubei Province is one of the major SFTS epidemic areas in the central part of China. This study reported the isolation of 11 new SFTSV strains from patients in Hubei Province collected in 2017. Extensive phylogenetic analyses were conducted based on the complete coding sequences of SFTSV segments including the new strains. It was suggested that five different SFTSV genotypes were circulating in Hubei, and 15 reassortment patterns and migration pathways correlated with each genotype were identified, which was more than previously recognized. Hubei Province was more involved in the evolutionary events of SFTSV than that previously thought in which the evolutionary events of SFTSV were reported to be independent from those in other epidemic regions. Further divergence of SFTSV strains was suggested by pairwise comparison of SFTSV sequences from each genotype and sequence identity normalized to representative strain in genotype C1. Subsequently, amino acid variations specific for genotype(s), strain(s), or cluster(s) were inspected, which may be related to differential biological activity of SFTSV strains/genotypes. In conclusion, we analyzed the current status of SFTSV phylogeny in Hubei Province and discussed the possible events correlated to SFTSV evolution. It provided an in-depth insight into SFTSV evolution, raising concerns for the use of proper SFTSV strains in future studies.

Nef Obtained from Individuals with HIV-1 Vary in Their Ability to Antagonize SERINC3- and SERINC5-Mediated HIV-1 Restriction.

Nef is a multifunctional viral protein that has the ability to downregulate cell surface molecules, including CD4 and major histocompatibility complex class I (MHC-I) and, as recently shown, also members of the serine incorporator family (SERINC). Here, we analyzed the impact of naturally occurring mutations in HIV-1 Nef on its ability to counteract SERINC restriction and the clinical course of infection. HIV-1 Nef sequences were obtained from 123 participants of the Amsterdam Cohort Studies and showed multiple amino acid variations and mutations. Most of the primary Nef proteins showed increased activity to counteract SERINC3 and SERINC5 as compared to NL4-3 Nef. Several mutations in Nef were associated with either an increased or decreased infectivity of Bal26-pseudotyped HIV-1 produced in the presence of SERINC3 or SERINC5. The 8R, 157N and R178G Nef mutations were shown to have an effect on disease progression. Survival analysis showed an accelerated disease progression of individuals infected with HIV-1 carrying arginine or asparagine at position 8 or 157 in Nef, respectively, or the R178G Nef mutation. Here, we observed that naturally occurring mutations in Nef affect the ability of Nef to counteract SERINC3- and SERINC5-mediated inhibition of viral infectivity. The majority of these Nef mutations had no significant effect on HIV-1 pathogenesis and only the 8R, 157N and R178G mutations were associated with disease course.

Molecular epidemiology analysis of early variants of SARS-CoV-2 reveals the potential impact of mutations P504L and Y541C (NSP13) in the clinical COVID-19 outcomes.

Since severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused global pandemic with alarming speed, comprehensively analyzing the mutation and evolution of early SARS-CoV-2 strains contributes to detect and prevent such virus. Here, we explored 1962 high-quality genomes of early SARS-CoV-2 strains obtained from 42 countries before April 2020. The changing trends of genetic variations in SARS-CoV-2 strains over time and country were subsequently identified. In addition, viral genotype mapping and phylogenetic analysis were performed to identify the variation features of SARS-CoV-2. Results showed that 57.89% of genetic variations involved in ORF1ab, most of which (68.85%) were nonsynonymous. Haplotype maps and phylogenetic tree analysis showed that amino acid variations in ORF1ab (p.5828P > L and p.5865Y > C, also NSP13: P504L and NSP13: Y541C) were the important characteristics of such clade. Furthermore, these variants showed more significant aggregation in the United States (P = 2.92E-66, 95%) than in Australia or Canada, especially in strains from Washington State (P = 1.56E-23, 77.65%). Further analysis demonstrated that the report date of the variants was associated with the date of increased infections and the date of recovery and fatality rate change in the United States. More importantly, the fatality rate in Washington State was higher (4.13%) and showed poorer outcomes (P = 4.12E-21 in fatality rate, P = 3.64E-29 in death and recovered cases) than found in other states containing a small proportion of strains with such variants. Using sequence alignment, we found that variations at the 504 and 541 sites had functional effects on NSP13. In this study, we comprehensively analyzed genetic variations in SARS-CoV-2, gaining insights into amino acid variations in ORF1ab and COVID-19 outcomes.

Generation and Characterization of Mouse Models of C3 Glomerulonephritis With CFI D288G and P467S Mutations.

C3 glomerulopathy (C3GP) is a disease entity caused by abnormality of the complement alternative pathway (AP) and characterized by C3 deposition in glomeruli. Many variations or mutations of complement factors are believed to underlie the susceptibility to C3GP, but there is a lack of experimental evidence. We have recently reported a patient with C3 glomerulonephritis (C3GN) and compound heterozygosity of two novel variations in the complement factor (CFI). Here, we generated a mouse model to mimic the CFI variations for studying pathogenicity of CFI variations in C3GN development. We used the CRISPR/Cas9 system to make mutant mouse lines that carried D288G and P467S mutations in CFI, respectively, and crossed them to generate mice with compound heterozygosity of CFI D288G and P467S. The mice were all normal in either SPF (specific pathogen free) or regular environment. When treated with lipopolysaccharides (LPS), a bacterial endotoxin that mimics infection and sepsis, the mice developed albuminuria, kidney function impairment, and C3 glomerular deposition at levels comparable with the wild-type mice. The mice with other genotypes concerning CFI D288G and P467S were also tested in parallel. Unexpectedly, we found that the D288G homozygotes all developed severe mesangial deposition of C3 in the LPS model, indicating that CFI D288G variation was involved in the C3 deposition, a key feature of C3GN. The mouse lines generated in the present study can be used to further study the role of CFI variations in C3GN development; in addition, they may be used to screen and test infections and environmental factors capable of triggering C3GN.

Genetic and Molecular Characterization of a Self-Compatible Brassica rapa Line Possessing a New Class II S Haplotype.

Most flowering plants have evolved a self-incompatibility (SI) system to maintain genetic diversity by preventing self-pollination. The Brassica species possesses sporophytic self-incompatibility (SSI), which is controlled by the pollen- and stigma-determinant factors SP11/SCR and SRK. However, the mysterious molecular mechanism of SI remains largely unknown. Here, a new class II S haplotype, named BrS-325, was identified in a pak choi line '325', which was responsible for the completely self-compatible phenotype. To obtain the entire S locus sequences, a complete pak choi genome was gained through Nanopore sequencing and de novo assembly, which provided a good reference genome for breeding and molecular research in B. rapa. S locus comparative analysis showed that the closest relatives to BrS-325 was BrS-60, and high sequence polymorphism existed in the S locus. Meanwhile, two duplicated SRKs (BrSRK-325a and BrSRK-325b) were distributed in the BrS-325 locus with opposite transcription directions. BrSRK-325b and BrSCR-325 were expressed normally at the transcriptional level. The multiple sequence alignment of SCRs and SRKs in class II S haplotypes showed that a number of amino acid variations were present in the contact regions (CR II and CR III) of BrSCR-325 and the hypervariable regions (HV I and HV II) of BrSRK-325s, which may influence the binding and interaction between the ligand and the receptor. Thus, these results suggested that amino acid variations in contact sites may lead to the SI destruction of a new class II S haplotype BrS-325 in B. rapa. The complete SC phenotype of '325' showed the potential for practical breeding application value in B. rapa.

Quality control of single amino acid variations detected by tandem mass spectrometry.

Study of single amino acid variations (SAVs) of proteins, resulting from single nucleotide polymorphisms, is of great importance for understanding the relationships between genotype and phenotype. In mass spectrometry based shotgun proteomics, identification of peptides with SAVs often suffers from high error rates on the variant sites detected. These site errors are due to multiple reasons and can be confirmed by manual inspection or genomic sequencing. Here, we present a software tool, named SAVControl, for site-level quality control of variant peptide identifications. It mainly includes strict false discovery rate control of variant peptide identifications and variant site verification by unrestrictive mass shift relocalization. SAVControl was validated on three colorectal adenocarcinoma cell line datasets with genomic sequencing evidences and tested on a colorectal cancer dataset from The Cancer Genome Atlas. The results show that SAVControl can effectively remove false detections of SAVs. SIGNIFICANCE: Protein sequence variations caused by single nucleotide polymorphisms (SNPs) are single amino acid variations (SAVs). The investigation of SAVs may provide a chance for understanding the relationships between genotype and phenotype. Mass spectrometry (MS) based proteomics provides a large-scale way to detect SAVs. However, using the current analysis strategy to detect SAVs may lead to high rate of false positives. The SAVControl we present here is a computational workflow and software tool for site-level quality control of SAVs detected by MS. It accesses the confidence of detected variant sites by relocating the mass shift responsible for an SAV to search for alternative interpretations. In addition, it uses a strict false discovery rate control method for variant peptide identifications. The advantages of SAVControl were demonstrated on three colorectal adenocarcinoma cell line datasets and a colorectal cancer dataset. We believe that SAVControl will be a powerful tool for computational proteomics and proteogenomics.

Detection of Unknown Amino Acid Substitutions Using Error-Tolerant Database Search.

Recent studies have demonstrated that mass spectrometry-based variant detection is feasible. Typically, either genomic variant databases or transcript data are used to construct customized target databases for the identification of single-amino acid variants in mass spectrometry data. However, both approaches require additional data to perform the identification of SAAVs. Here, we discuss the application of an error-tolerant peptide search engine such as BICEPS for identifying variants exclusively based on standard Uniprot databases. Thereby, unnecessary and redundant extensions of the search space are avoided. The workflow provides an unbiased view on the data; the search space is not limited to known variants and simultaneously does not require additional data. In a subsequent step a second identification search is performed to verify the initially identified variant peptides and aggregate information on the protein level.

Genetic dissection of complete genomes of Type 2 PRRS viruses isolated in Denmark over a period of 15 years.

Type 2 Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) was first detected in Europe in 1996 co-incident with the introduction of a live attenuated vaccine. Since then, only limited ORF5 and ORF7 sequences of Type 2 PRRS viruses have been reported throughout Europe. In the present study, the genetic and antigenic diversity of 11 complete genomes and 49 ORF5 and 55 ORF7 nucleotide sequences obtained from 57 viruses in Denmark from 2003 to 2012 were examined. The genetic identity of the 11 complete genomes to the vaccine strain (Ingelvac PRRS MLV) ranged between 93.6 and 99.6% while the 49 ORF5 sequences examined were 94.0-99.8% identical to the vaccine strain. Among the Danish sequences, the pairwise nucleotide identity was 90.9-100% and 93.0-100.0% for ORF5 and ORF7, respectively. Analysis of the genetic region encoding NSP2 revealed high diversity among the Danish viruses with an 86.6-98.9% range in similarity. Furthermore, several of the sequenced viruses harbored deletions in the NSP2 coding region. Phylogenetic analysis in a global Type 2 PRRSV framework classified all Danish isolates to a single cluster (sub-lineage 5.1) which comprised strains closely-related to the Type 2 prototype isolate VR2332.

Expression of Hepatitis B virus surface antigen (HBsAg) from genotypes A, D and F and influence of amino acid variations related or not to genotypes on HBsAg detection

The impact of hepatitis B virus (HBV) genotypes on the sensitivity of surface antigen (HBsAg) detection assays has been poorly investigated. Here, plasmids carrying consensus or variant coding sequences for HBV surface proteins from genotypes A, D and F, were constructed. HBsAg levels were evaluated in medium and extracts of transfected CHO cells by a commercial polyclonal-based assay. We show that HBsAg detection values of consensus forms from genotypes D and F were, respectively, 37 percent and 30 percent lower than those obtained by genotype A. However, the presence of two single variations, T143M in genotype A, and T125M in genotype D, produced a decrease of 44 percent and an increase of 34 percent, respectively, on HBsAg mean values in comparison with their consensus forms. In conclusion, HBsAg detection levels varied among HBV genotypes. However, unique amino acid substitutions not linked to genotypes, such as T125M and T143M described here, should have more implications in HBV immunological diagnostics than the set of variations characteristic of each HBV genotype.