Bioinformatics Databases Research Articles

Genomic analysis of SARS-CoV-2 Circulating during Second and Third Wave of COVID-19 in Nepal.

In Nepal, since the first detection of COVID-19 case in January 2020, the total cases have rose to almost a million with more than 12,000 deaths. Till now, WHO has classified 5 variants of SARS-Cov2 as variant of concerns at different time points causing many waves in different countries and regions at different time points. Nepal had also faced three distinct waves of COVID-19 caused by different variant of COVID 19. The objective of this study was to perform whole-genome sequencing of SARS-CoV-2 circulating in different waves of COVID-19 in Nepal and investigate its variant or lineage. In this study, samples from 49 SARS-CoV-2 infected subjects from May 2021 to January 2022, were investigated. The methodology followed RNA extraction, real-time PCR for confirmation and whole-genome sequencing. The consensus genomes were interpreted with appropriate bioinformatics tools and databases. Sequence analysis of 49 genomes revealed to be of Delta (n=27) and Omicron Variant (n=22). The mutations in the consensus genomes contained the defining mutations of the respective lineages/variants. There were 20 genomes of Omicron sub-lineage BA.2, 1 of BA.1.1 and 1 of B.1.1.529. This study provides concise genomic evidence of presence of Delta and Omicron variant of COVID-19 in Nepal. Delta and Omicron variants were driving the second wave and the third wave of COVID-19 respectively in Nepal. Therefore, the genomic surveillance must be increased to clearly map out the pandemic and strategize vaccination approaches in the country.

MALAT1-regulated gene expression profiling in lung cancer cell lines

BackgroundNon-small cell lung cancer (NSCLC) is the most common type of lung cancer and has a poor prognosis. Identifying biomarkers based on molecular mechanisms is critical for early diagnosis, timely treatment, and improved prognosis of lung cancer. MALAT1 has been reported to have overexpressed and tumor-promoting functions in NSCLC. It has been proposed as a potential biomarker for the diagnosis and prognosis of cancer. Therefore, this study was conducted to profile the changes in gene expression according to the regulation of expression of MALAT1 in NSCLC cell lines and to investigate the correlation through bioinformatic analysis of differentially expressed genes (DEGs).MethodsMALAT1 expression levels were measured using RT-qPCR. The biological functions of MALAT1 in NSCLC were analyzed by cell counting, colony forming, wound-healing, and Transwell invasion assays. In addition, gene expression profiling in response to the knockdown of MALAT1 was analyzed by transcriptome sequencing, and differentially expressed genes regulated by MALAT1 were performed by GO and KEGG pathway enrichment analyses. Bioinformatic databases were used for gene expression analysis and overall survival analysis.ResultsComparative analysis versus MALAT1 expression in MRC5 cells (a normal lung cell line) and the three NSCLC cell lines showed that MALAT1 expression was significantly higher in the NSCLC cells. MALAT1 knockdown decreased cell survival, proliferation, migration, and invasion in all three NSCLC cell lines. RNA-seq analysis of DEGs in NSCLC cells showed 198 DEGs were upregulated and 266 DEGs downregulated by MALAT1 knockdown in all three NSCLC cell lines. Survival analysis on these common DEGs performed using the OncoLnc database resulted in the selection of five DEGs, phosphoglycerate mutase 1 (PGAM1), phosphoglycerate mutase 4 (PGAM4), nucleolar protein 6 (NOL6), nucleosome assembly protein 1 like 5 (NAP1L5), and sestrin1 (SESN1). The gene expression levels of these selected DEGs were proved to gene expression analysis using the TNMplot database.ConclusionMALAT1 might function as an oncogene that enhances NSCLC cell survival, proliferation, colony formation, and invasion. RNA-seq and bioinformatic analyses resulted in the selection of five DEGs, PGAM1, PGAM4, NOL6, NAP1L5, and SESN1, which were found to be closely related to patient survival and tumorigenesis. We believe that further investigation of these five DEGs will provide valuable information on the oncogenic role of MALAT1 in NSCLC.

Prognostic and clinicopathological significance of MRC2 expression in head and neck squamous cell carcinoma

BackgroundHead and neck squamous cell carcinoma (HNSCC) is one of the most aggressive types of cancers worldwide, with metastasis being the major cause of death. Recent research suggests that changes in the expression of MRC2 (mannose receptor, C-type 2) may play a role in the development and progression of various cancers; however, its expression pattern in HNSCC/ OSCC is unknown. This study aimed to elucidate the clinicopathological significance and prognostic role of MRC2 expression in HNSCC, including OSCC. Materials and methodsIn the present study, we assessed the potential roles of MRC2 in expression, prognostic value, immune infiltration and functional enrichment analysis in HNSCC patients by using different bioinformatics databases. We then validated MRC2 gene expression in 30 OSCC and adjacent normal tissue samples using quantitative reverse transcription PCR (RT-qPCR). ResultsMRC2 mRNA and protein expression were significantly upregulated in OSCC and HNSCC patients compared to that in adjacent normal tissues. Upregulated MRC2 expression was associated with poor overall survival. Increased MRC2 expression has also been linked to an aggressive clinicopathological features including advanced stages, grade, metastasis and HPV status. Interestingly, our in silico results strongly suggest that the MRC2 gene and protein interaction networks are associated with HNSCC development. Moreover, the tumor infiltration level was significantly correlated with HPV-negative HNSCC patients. ConclusionOur results suggest that MRC2 could be used as a novel prognostic marker and therapeutic target for HNSCC.

Retention Time and Fragmentation Predictors Increase Confidence in Identification of Common Variant Peptides.

Precision medicine focuses on adapting care to the individual profile of patients, for example, accounting for their unique genetic makeup. Being able to account for the effect of genetic variation on the proteome holds great promise toward this goal. However, identifying the protein products of genetic variation using mass spectrometry has proven very challenging. Here we show that the identification of variant peptides can be improved by the integration of retention time and fragmentation predictors into a unified proteogenomic pipeline. By combining these intrinsic peptide characteristics using the search-engine post-processor Percolator, we demonstrate improved discrimination power between correct and incorrect peptide-spectrum matches. Our results demonstrate that the drop in performance that is induced when expanding a protein sequence database can be compensated, hence enabling efficient identification of genetic variation products in proteomics data. We anticipate that this enhancement of proteogenomic pipelines can provide a more refined picture of the unique proteome of patients and thereby contribute to improving patient care.

Exploring the Interplay of Hypoxia-Inducible Factors: Unveiling Genetic Connections to Diseases Through Bioinformatics Analysis

Objective: Hypoxia-inducible factor (HIF) is a transcription factor that is effective in the ability of cells to sense and adapt to changes in oxygen levels. HIF1α gene is located in the 14q23.2 chromosome region and consists of 15 exons and 14 introns. It is a transcriptional regulator of metabolic processes such as angiogenesis and erythropoiesis and is required for immunological responses. Material and Methods: Our study examined the function of HIF1α and its relations with other genes and diseases using various bioinformatics database tools. GENEMANIA/GeneCard databases were used to detect the relationship of HIF gene with other genes, miRDB to show target miRNAs, STRING to detect protein-protein interaction, and GWAS databases to show its relationship with diseases. In addition, organs and tissues in which it is expressed were determined using the UniProt database. Results: The bioinformatic analysis yielded significant results, revealing that 189 miRNAs target HIF1α and exhibits close interactions with 10 genes, among which important genes like STAT3, MDM2, TP53, SMAD3, and VHL were identified. The most predominant pathway utilized by the HIF1α gene was determined to be the HIF-1 signaling pathway. A co-expression relationship was also established with proteins EPO, PLIN2, BNIP3, and the enzyme ENO1. Furthermore, it was ascertained that HIF1α exhibits the highest expression levels in the kidney and the perivenous region of the liver. Moreover, close associations have been established between HIF1α and diseases such as renal cell carcinoma and bladder cancer. Conclusion: Identifying the pathways associated with HIF1α, other genes, and epigenetic factors with the help of Bioinformatics Tools may enable experimental studies to be carried out with large cohorts and using a broad perspective. Thus, it may contribute to our understanding of how this gene affects diseases and anomalies and to accelerate the studies of targeted therapeutic treatment.

Potential Key Proteins, Molecular Networks, and Pathways in Perinatal Hypoxia.

Perinatal hypoxia is a common risk factor for CNS development. Using bioinformatics databases, a list of 129 genes involved in perinatal hypoxia was selected from the literature and analyzed with respect to proteins important for biological processes influencing the brain development. Functional enrichment analysis using the DAVID database was performed to identify relevant Gene Ontology (GO) biological processes like response to hypoxia, inflammatory response, positive and negative regulation of apoptosis, and positive and negative regulation of cell proliferation. The selected GO processes contain 17-30 proteins and show an enrichment of 6.3-14.3-fold. The STRING protein-protein interaction network and the Cytoscape data analyzer were used to identify interacting proteins playing a significant role in these processes. The two top protein pairs referring to the proteins with highest degrees and the corresponding proteins connected by high score edges exert opposite or regulatory functions and are essential for the balance between damaging, repairing, protective, or epigenetic processes. The GO response to hypoxia is characterized by the high score protein-protein interaction pairs CASP3/FAS promoting apoptosis and by the protective acting BDNF/MECP2 protein pair. Core components of the GO processes positive and negative regulation of apoptosis are the proteins CASP3/FAS/AKT/eNOS/RPS6KB1 involved in several signal pathways. The GO processes cell proliferation are characterized by the high-score protein-protein interaction pairs MYC/ MAPK1, JUN/MAPK1, IL6/IL1B, and JUN/HDAC1. The study provides new insights into the pathophysiology of perinatal hypoxia and is of importance for future investigations, diagnostics, and therapy of perinatal hypoxia.

Expression analysis, clinical significance and potential function of PLXNB2 in acute myeloid leukaemia.

The overall survival (OS) rate of adult patients suffering from acute myeloid leukaemia (AML) remains unsatisfactory at less than 40%. Current risk stratification systems fail to provide accurate guidelines for precise treatment. Novel biomarkers for predicting prognosis are urgently needed. Plexin B2 (PLXNB2), a functional receptor of angiogenin (ANG), has been found to be aberrantly expressed in multitudinous tumours. We detected overexpression of PLXNB2 mRNA in AML via transcriptome microarray analysis. This study aims to explore the potential role of PLXNB2 as a biomarker of prognosis and a prospective target of AML. qRT‒PCR was conducted to verify the expression of PLXNB2 mRNA in bone marrow mononuclear cells from AML patients. Immunohistochemical and immunofluorescence staining were performed and confirmed increased expression of PLXNB2 protein in AML bone marrow tissues. Data on PLXNB2 expression, prognosis and clinical features were accessed from multiple bioinformatic databases, including The Cancer Genome Atlas (TCGA). Genes coexpressed and correlated with PLXNB2 were identified and analysed in the TCGA AML cohort. Metascape was applied for functional and pathway enrichment analysis of genes related to PLXNB2. Small molecular agents and traditional Chinese medicines potentially targeting genes related to PLXNB2 were screened via the Connectivity Map, TCMSP and HIT databases. PLXNB2 mRNA and protein levels are higher in AML samples than in normal controls. Overexpression of PLXNB2 is associated with worse OS in AML. Patients with high PLXNB2 expression might benefit more from haematopoietic stem cell transplantation (HSCT) (indicated by prolonged OS) than those with only chemotherapy treatment. Differentially expressed genes between the high and low PLXNB2 expression groups were overlapped with PLXNB2-coexpressed genes, and genes that overlapped were enriched in immune functions, endothelial cell regulation and cell interaction gene sets, indicating the potential function of PLXNB2 in AML. A total of 36 hub genes were identified from the differentially expressed genes, and MRC1, IL10, CD163 and CCL22 had significant prognostic value for AML. Analysis of the connectivity map and traditional agents revealed that honokiol, morphines, triptolide and paeoniflorin could be potential treatment regimens. The overexpression of PLXNB2 is an adverse prognostic factor in adult AML patients and could be used as a potential biomarker. PLXNB2 might exert an oncogenic role by modulating immune functions, endothelial cell functions and cell interactions. AML patients with high PLXNB2 expression could benefit more from HSCT.

First Report of Calystegia hederacea as a new host of sweet potato leaf curl Hubei virus.

Calystegia hederacea (Convolvulaceae) is one of the most problematic perennial weeds widely distributed around or in crop fields. Our previous studies showed that C. hederacea is natural reservoir of sweet potato chlorotic stunt virus isolate CH (SPCSV-CH) and sweet potato latent virus (SPLV) (Liu et al. 2020; Zhao et al. 2022). To shed further light on the role of C. hederacea in the epidemiology of sweet potato viruses, in May 2021, a total of seven C. hederacea plants (five asymptomatic, one curling and one mild vein-clearing) were collected from two different sweet potato fields in Xinxiang city of Henan Province in China. Total RNA was prepared from a pool of the seven leaf samples using the EZNA Plant RNA Kit (Omega Bio-Tek, Norcross, GA). A library was constructed from the ribosomal-depleted RNA using the NEBNext Ultra Directional RNA Library Prep Kit for Illumina (NEB, MA, USA) and sequenced using the Illumina HiSeq platform (Novogene, Tianjin, China). A total of 139,057,020 paired-end clean reads of 150 bp were obtained after removing adaptor sequences and low-quality reads and used for de novo assembly using the Trinity (v2.2.0) software. Blast searches of the assembled contigs longer than 200 bp against NCBI nucleotide and protein sequence databases revealed the presence of 37 contigs (237 to 4885 bp) and 19 contigs (261 to 758 bp) with high nucleotide (nt) identity with SPLV and SPCSV-CH, respectively. The occurrence of SPLV and SPCSV-CH on C. hederacea was previously reported, and thus the contig sequences related to SPLV and SPCSV-CH were not subjected to further verification in this study. In addition, one contig (2,827 bp) with the highest nt sequence identity of 94.94% with sweet potato leaf curl Hubei virus (SPLCHbV, genus Begomovirus, family Geminiviridae, accession no. MK931304) was assembled from 16,592 reads, with average coverage depth of 740.5X. These results suggested the presence of SPLCHbV in C. hederacea. To further confirm the RNA sequencing result, each of the seven samples was tested by PCR using partially overlapping (italicized nucleotides) forward and reverse primers (SweeIn-F1, 5`-GGAGGAAGCTAAGTACGAGAATCAGTTAGAG-3`; SweeIn-R1, 5`-GCTTCCTCCTTGTGATTGTAAGTAACATGG-3`) that were designed based on the SPLCHbV-related contig for amplification of circular DNA viral genome (approximately 2.7 kb). Two symptomatic and three symptomless C. hederacea samples were SPLCHbV positive, indicating that virus-like symptoms of the two C. hederacea samples were probably not induced by SPLCHbV. Two of the five amplified products were completely sequenced and deposited to GenBank (accession nos. OQ551733 and OQ551734). Sequences analysis showed that the complete genome sequences of two SPLCHbV C. headrace isolates (2,763 nt and 2,761 nt) had 96.53% nt identity with each other and 95.92 to 97.70% nt identity with that of SPLCHbV isolate Shandong7-2017 (MK931304). In August 2021, fourteen C. hederacea plants (three symptomatic, 11 asymptomatic) collected from natural fields from Zhumadian and Pingdingshan cities in Henan Province, were tested by PCR using SweeIn-F1/R1 primers for SPLCHbV, showing that eight samples were SPLCHbV positive. SPLCHbV belongs to the sweepoviruses, a group of phylogenetically distinct begomoviruses infecting sweet potato, and was reported to infect sweet potato from many provinces of China (Wang et al., 2021). To the best of our knowledge, this is the first report of SPLCHbV infection in C. hederacea, which expands the natural host range of SPLCHbV.

MYH16 upregulation is associated with lung adenocarcinoma aggressiveness and immune infiltration.

Myosin heavy chain 16 (MYH16) may significantly affect cell cycle progression. Nevertheless, there is a lack of evidence about the clinical relevance of MYH16 upregulation in pan cancers, including lung adenocarcinoma (LUAD). MYH16 expression patterns were evaluated in various bioinformatics databases using The Cancer Genome Atlas data set. Clinical and pathological factor data were employed to risk-stratify patients. The Kaplan-Meier plotter approach was used to estimate survival rates. Tumor immune infiltration was explored via the TIMER tool, and gene set enrichment analysis (GSEA) was used to identify the pathways involved in MYH16 upregulation. The results showed that MYH16 was abnormally upregulated in pan cancers, including LUAD. MYH16 expression induction in LUAD was found to be related to the tumor stage. Furthermore, MYH16 upregulation was correlated with LUAD development and worse overall survival, particularly in women. Notably, MYH16 overexpression in LUAD tissues corresponded to the amount of immune infiltration in the tumor. Additionally, univariate Cox hazard regression analysis revealed that MYH16 may be an independent prognostic indicator for LUAD. Furthermore, a nomogram was constructed according to MYH16 expression and clinical characteristics. BMP6 expression deficiency may be a key factor contributing to MYH16 upregulation in LUAD. Finally, GSEA demonstrated that MYH16 might mediate meiosis and gene silencing through RNA signaling pathways. This study, for the first time, showed that MYH16 upregulation in LUAD is associated with various risk factors, increased cancer aggressiveness, enhanced infiltration of tumor immune cells, and reduced survival rates.

Mutational analysis of hemoglobin genes and functional characterization of detected variants, through in-silico analysis, in Pakistani beta-thalassemia major patients

Thalassemia is one of the most prevalent genetic disorders worldwide. The present study aimed to explore the mutational spectrum of all hemoglobin (HB) encoding genes and to identify the potentially damaging and pathogenic variants in the beta (β)-thalassemia major patients and thalassemia minor carriers of Southern Punjab, Pakistan. A total of 49 β-thalassemia major patients and 49 carrier samples were screened for the identification of HBA1, HBA2, HBB, HBD, HBE1, HBG1 and HBG2 variants by NGS. PCR was performed for the amplification of HB encoding genes and the amplified product of 13 patients and 7 carrier samples were processed for the Sanger sequencing. Various bioinformatics tools and databases were employed to reveal the functional impact and pathogenicity potential of the observed variants. Results depicted a total of 20 variants of HB-related genes by NGS and 5 by Sanger sequencing in thalassemia patients. While 20 variants by NGS and 3 by Sanger were detected in carriers. Few known genetic variants of HB-encoding genes are being reported for the first time in Pakistani thalassemia patients and carriers. However, two novel HBB variants c.375A>C (p.P125P) and c.*61T>G and a novel variant of HBE1 (c.37A>T (p.T13S)) were also documented. Pathogenicity analysis predicted the pathogenic potential of HBB variants (c.47G>A (p.W16*), c.27-28insG (p. S10fs), and c.92+5G>C) for β thalassemia. The study of functional impact indicated that these HBB variants result in the premature termination of translation leading to the loss of functional β-globin protein. It is therefore suggested that the pathogenic HBB variants, identified during present study, can be employed for the diagnosis, carrier screening, and planning therapy of thalassemia.

Bioinformatic and literature assessment of toxicity and allergenicity of a CRISPR-Cas9 engineered gene drive to control Anopheles gambiae the mosquito vector of human malaria

BackgroundPopulation suppression gene drive is currently being evaluated, including via environmental risk assessment (ERA), for malaria vector control. One such gene drive involves the dsxFCRISPRh transgene encoding (i) hCas9 endonuclease, (ii) T1 guide RNA (gRNA) targeting the doublesex locus, and (iii) DsRed fluorescent marker protein, in genetically-modified mosquitoes (GMMs). Problem formulation, the first stage of ERA, for environmental releases of dsxFCRISPRh previously identified nine potential harms to the environment or health that could occur, should expressed products of the transgene cause allergenicity or toxicity.MethodsAmino acid sequences of hCas9 and DsRed were interrogated against those of toxins or allergens from NCBI, UniProt, COMPARE and AllergenOnline bioinformatic databases and the gRNA was compared with microRNAs from the miRBase database for potential impacts on gene expression associated with toxicity or allergenicity. PubMed was also searched for any evidence of toxicity or allergenicity of Cas9 or DsRed, or of the donor organisms from which these products were originally derived.ResultsWhile Cas9 nuclease activity can be toxic to some cell types in vitro and hCas9 was found to share homology with the prokaryotic toxin VapC, there was no evidence from previous studies of a risk of toxicity to humans and other animals from hCas9. Although hCas9 did contain an 8-mer epitope found in the latex allergen Hev b 9, the full amino acid sequence of hCas9 was not homologous to any known allergens. Combined with a lack of evidence in the literature of Cas9 allergenicity, this indicated negligible risk to humans of allergenicity from hCas9. No matches were found between the gRNA and microRNAs from either Anopheles or humans. Moreover, potential exposure to dsxFCRISPRh transgenic proteins from environmental releases was assessed as negligible.ConclusionsBioinformatic and literature assessments found no convincing evidence to suggest that transgenic products expressed from dsxFCRISPRh were allergens or toxins, indicating that environmental releases of this population suppression gene drive for malaria vector control should not result in any increased allergenicity or toxicity in humans or animals. These results should also inform evaluations of other GMMs being developed for vector control and in vivo clinical applications of CRISPR-Cas9.

The diagnostic potential of two exosome-derived circRNAs for papillary thyroid cancer.

As a critical component of exosomes, circular RNAs (circRNAs) have shown great value in cancer diagnosis. This study aimed to identify circRNAs in exosomes for the diagnosis of PTC (papillary thyroid carcinoma). We selected hsa_circ_0082002 and hsa_circ_0003863 based on circRNA microarray. The levels of exosomal hsa_circ_0082002 and hsa_circ_0003863 in the sera of healthy control (n = 68), benign thyroid tumors (n = 60), and PTC without and with Hashimoto's thyroiditis (n = 164) were quantified by qPCR (quantitative polymerase chain reaction). Receiver operating characteristic analyses were conducted to evaluate the diagnostic sensitivity and specificity. Bioinformatics databases were used to predict the microRNAs and proteins binding with hsa_circ_0082002 and hsa_circ_0003863. The levels of exosomal hsa_circ_0082002 and hsa_circ_0003863 were positively associated and statistically increased in PTC compared to healthy and benign thyroid tumors. Intriguingly, higher levels of exosomal hsa_circ_0082002 and hsa_circ_0003863 were positively correlated with lymph node metastasis and vascular invasion in PTC. Further stability tests show that exosomal hsa_circ_0082002 and hsa_circ_0003863 could exist stably in sera treated by several freeze-thaw cycles at -20°C and with a storage time shorter than 24h at 4°C. Furthermore, hsa_circ_0082002 and hsa_circ_0003863 were predicted to interact with microRNAs and proteins, suggesting that hsa_circ_0082002 and hsa_circ_0003863 might contribute to the occurrence and progression of PTC through interacting with microRNAs and RNA binding proteins. Collectively, we identified two PTC-related circRNAs incorporated in exosomes and uncovered their potential as tumor markers to diagnose PTC, in particular, more aggressive PTC.

MetaSpectraST: an unsupervised and database-independent analysis workflow for metaproteomic MS/MS data using spectrum clustering

BackgroundThe high diversity and complexity of the microbial community make it a formidable challenge to identify and quantify the large number of proteins expressed in the community. Conventional metaproteomics approaches largely rely on accurate identification of the MS/MS spectra to their corresponding short peptides in the digested samples, followed by protein inference and subsequent taxonomic and functional analysis of the detected proteins. These approaches are dependent on the availability of protein sequence databases derived either from sample-specific metagenomic data or from public repositories. Due to the incompleteness and imperfections of these protein sequence databases, and the preponderance of homologous proteins expressed by different bacterial species in the community, this computational process of peptide identification and protein inference is challenging and error-prone, which hinders the comparison of metaproteomes across multiple samples.ResultsWe developed metaSpectraST, an unsupervised and database-independent metaproteomics workflow, which quantitatively profiles and compares metaproteomics samples by clustering experimentally observed MS/MS spectra based on their spectral similarity. We applied metaSpectraST to fecal samples collected from littermates of two different mother mice right after weaning. Quantitative proteome profiles of the microbial communities of different mice were obtained without any peptide-spectrum identification and used to evaluate the overall similarity between samples and highlight any differentiating markers. Compared to the conventional database-dependent metaproteomics analysis, metaSpectraST is more successful in classifying the samples and detecting the subtle microbiome changes of mouse gut microbiomes post-weaning. metaSpectraST could also be used as a tool to select the suitable biological replicates from samples with wide inter-individual variation.ConclusionsmetaSpectraST enables rapid profiling of metaproteomic samples quantitatively, without the need for constructing the protein sequence database or identification of the MS/MS spectra. It maximally preserves information contained in the experimental MS/MS spectra by clustering all of them first and thus is able to better profile the complex microbial communities and highlight their functional changes, as compared with conventional approaches. tag the videobyte in this section as ESM45SRGQ1P3pEwLWJemohrVpiVideo

The Association of Biomolecular Resource Facilities Proteome Informatics Research Group Study on Metaproteomics (iPRG-2020).

Metaproteomics research using mass spectrometry data has emerged as a powerful strategy to understand the mechanisms underlying microbiome dynamics and the interaction of microbiomes with their immediate environment. Recent advances in sample preparation, data acquisition, and bioinformatics workflows have greatly contributed to progress in this field. In 2020, the Association of Biomolecular Research Facilities Proteome Informatics Research Group launched a collaborative study to assess the bioinformatics options available for metaproteomics research. The study was conducted in 2 phases. In the first phase, participants were provided with mass spectrometry data files and were asked to identify the taxonomic composition and relative taxa abundances in the samples without supplying any protein sequence databases. The most challenging question asked of the participants was to postulate the nature of any biological phenomena that may have taken place in the samples, such as interactions among taxonomic species. In the second phase, participants were provided a protein sequence database composed of the species present in the sample and were asked to answer the same set of questions as for phase 1. In this report, we summarize the data processing methods and tools used by participants, including database searching and software tools used for taxonomic and functional analysis. This study provides insights into the status of metaproteomics bioinformatics in participating laboratories and core facilities.

PlantMetSuite: A User-Friendly Web-Based Tool for Metabolomics Analysis and Visualisation.

The advancement of mass spectrometry technologies has revolutionised plant metabolomics research by enabling the acquisition of raw metabolomics data. However, the identification, analysis, and visualisation of these data require specialised tools. Existing solutions lack a dedicated plant-specific metabolite database and pose usability challenges. To address these limitations, we developed PlantMetSuite, a web-based tool for comprehensive metabolomics analysis and visualisation. PlantMetSuite encompasses interactive bioinformatics tools and databases specifically tailored to plant metabolomics data, facilitating upstream-to-downstream analysis in metabolomics and supporting integrative multi-omics investigations. PlantMetSuite can be accessed directly through a user's browser without the need for installation or programming skills. The tool is freely available and will undergo regular updates and expansions to incorporate additional libraries and newly published metabolomics analysis methods. The tool's significance lies in empowering researchers with an accessible and customisable platform for unlocking plant metabolomics insights.

Long noncoding RNA BBOX1-AS1 increased radiotherapy sensitivity in colorectal cancer by stabilizing and activating PFK1

PurposeOur study explored the effect of long noncoding RNA BBOX1-AS1 on colorectal cancer (CRC) radiosensitivity in vivo and in vitro. MethodsDifferentially expressed lncRNAs in CRC were screened using a bioinformatics database and an online prediction website. The expression of BBOX1-AS1 in tissue samples was analyzed via real-time quantitative PCR (RT-qPCR). Subcellular localization of BBOX1-AS1 in CRC cells was analyzed using fluorescence in situ hybridization (FISH). The correlation between BBOX1-AS1 and PFK1 expression levels in CRC tissues was analyzed via Pearson's correlation coefficient. The effect of BBOX1-AS1 on PFK1 stability was investigated using RNA and protein stability testing. RNA Binding Protein Immunoprecipitation (RIP) and RNA pull-down assays were used to confirm the binding of BBOX1-AS1 to PFK1. ResultsBBOX1-AS1 was highly expressed in CRC and associated with poor prognosis. Similarly, it was highly expressed in CRC tissues and CRC cell lines. In addition, BBOX1-AS1 promoted the proliferation, invasion, migration, and glycolysis of CRC cells and inhibited apoptosis. RIP and RNA pull-down experiments confirmed that BBOX1-AS1 bound to PFK1. RNA stability and protein stability experiments showed that BBOX1-AS1 affected the stability of PFK1 mRNA and protein. Furthermore, we confirmed that BBOX1-AS1 increased radiation resistance through the regulation of PFK1 expression. ConclusionsBBOX1-AS1 promoted the proliferation, invasion, migration, and glycolysis of CRC cells through stabilization of the expression of PFK1. BBOX1-AS1 also inhibited CRC cell apoptosis and increased radiotherapy resistance in CRC cells.

Screening and identification of potential biomarkers for pancreatic cancer: An integrated bioinformatics analysis

Pancreatic cancer is one of the highly invasive and the seventh most common cause of death among cancers worldwide. To identify essential genes and the involved mechanisms in pancreatic cancer, we used bioinformatics analysis to identify potential biomarkers for pancreatic cancer management. Gene expression profiles of pancreatic cancer patients and normal tissues were screened and downloaded from The Cancer Genome Atlas (TCGA) bioinformatics database. The Differentially expressed genes (DEGs) were identified among gene expression signatures of normal and pancreatic cancer, using R software. Then, enrichment analysis of the DEGs, including Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, was performed by an interactive and collaborative HTML5 gene list enrichment analysis tool (enrichr) and ToppGene. The protein-protein interaction (PPI) network was also constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) database and ToppGenet web based tool followed by identifying hub genes of the top 100 DEGs in pancreatic cancer using Cytoscape software. Over 2000 DEGs with variable log2 fold (LFC) were identified among 34,706 genes. Principal component analysis showed that the top 20 DEGs, including H1–4, H1–5, H4C3, H4C2, RN7SL2, RN7SL3, RN7SL4P, RN7SKP80, SCARNA12, SCARNA10, SCARNA5, SCARNA7, SCARNA6, SCARNA21, SCARNA9, SCARNA13, SNORA73B, SNORA53, SNORA54 might distinguish pancreatic cancer from normal tissue. GO analysis showed that the top DEGs have more enriched in the negative regulation of gene silencing, negative regulation of chromatin organization, negative regulation of chromatin silencing, nucleosome positioning, regulation of chromatin silencing, and nucleosomal DNA binding. KEGG analysis identified an association between pancreatic cancer and systemic lupus erythematosus, alcoholism, neutrophil extracellular trap formation, and viral carcinogenesis. In PPI network analysis, we found that the different types of histone-encoding genes are involved as hub genes in the carcinogenesis of pancreatic cancer. In conclusion, our bioinformatics analysis identified genes that were significantly related to the prognosis of pancreatic cancer patients. These genes and pathways could serve as new potential prognostic markers and be used to develop treatments for pancreatic cancer patients.

Database Creator for Mass Analysis of Peptides and Proteins, DC-MAPP: A Standalone Tool for Simplifying Manual Analysis of Mass Spectral Data to Identify Peptide/Protein Sequences.

Proteomic studies typically involve the use of different types of software for annotating experimental tandem mass spectrometric data (MS/MS) and thereby simplifying the process of peptide and protein identification. For such annotations, these softwares calculate the m/z values of the peptide/protein precursor and fragment ions, for which a database of protein sequences must be provided as an input file. The calculated m/z values are stored as another database, which the user usually cannot view. Database Creator for Mass Analysis of Peptides and Proteins (DC-MAPP) is a novel standalone software that can create custom databases for "viewing" the calculated m/z values of precursor and fragment ions, prior to the database search. It contains three modules. Peptide/Protein sequences as per user's choice can be entered as input to the first module for creating a custom database. In the second module, m/z values must be queried-in, which are searched within the custom database to identify protein/peptide sequences. The third module is suited for peptide mass fingerprinting, which can be used to analyze both ESI and MALDI mass spectral data. The feature of "viewing" the custom database can be helpful not only for better understanding the search engine processes, but also for designing multiple reaction monitoring (MRM) methods. Post-translational modifications and protein isoforms can also be analyzed. Since, DC-MAPP relies on the protein/peptide "sequences" for creating custom databases, it may not be applicable for the searches involving spectral libraries. Python language was used for implementation, and the graphical user interface was built with Page/Tcl, making this tool more user-friendly. It is freely available at https://vit.ac.in/DC-MAPP/.

Identification of Drug Targets and Agents Associated with Hepatocellular Carcinoma through Integrated Bioinformatics Analysis.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death globally. The mechanisms underlying the development of HCC are mostly unknown till now. The main goal of this study was to identify potential drug target proteins and agents for the treatment of HCC. The publicly available three independent mRNA expression profile datasets were downloaded from the NCBI-GEO database to explore common differentially expressed genes (cDEGs) between HCC and control samples using the Statistical LIMMA approach. Hub-cDEGs as drug targets highlighting their functions, pathways, and regulators were identified by using integrated bioinformatics tools and databases. Finally, Hub-cDEGs-guided top-ranked drug agents were identified by molecular docking study for HCC. We identified 160 common DEGs (cDEGs) from three independent mRNA expression datasets in which ten cDEGs (CDKN3, TK1, NCAPG, CDCA5, RACGAP1, AURKA, PRC1, UBE2T, MELK, and ASPM) were selected as Hub-cDEGs. The GO functional and KEGG pathway enrichment analysis of Hub-cDEGs revealed some crucial cancer-stimulating biological processes, molecular functions, cellular components, and signaling pathways. The interaction network analysis identified three TF proteins and five miRNAs as the key transcriptional and post-transcriptional regulators of HubcDEGs. Then, we detected the proposed Hub-cDEGs guided top-ranked three anti-HCC drug molecules (Dactinomycin, Vincristine, Sirolimus) that were also highly supported by the already published top-ranked HCC-causing Hub-DEGs mediated receptors. The findings of this study would be useful resources for diagnosis, prognosis, and therapies of HCC.

New protein families with hendecad coiled coils in the proteome of life

Coiled coils are a widespread and well understood protein fold. Their short and simple repeats underpin considerable structural and functional diversity. The vast majority of coiled coils consist of 7-residue (heptad) sequence repeats, but in essence most combinations of 3- and 4-residue segments, each starting with a residue of the hydrophobic core, are compatible with coiled-coil structure. The most frequent among these other repeat patterns are 11-residue (hendecad, 3 + 4 + 4) repeats. Hendecads are frequently found in low copy number, interspersed between heptads, but some proteins consist largely or entirely of hendecad repeats. Here we describe the first large-scale survey of these proteins in the proteome of life. For this, we scanned the protein sequence database for sequences with 11-residue periodicity that lacked β-strand prediction. We then clustered these by pairwise similarity to construct a map of potential hendecad coiled-coil families. Here we discuss these according to their structural properties, their potential cellular roles, and the evolutionary mechanisms shaping their diversity. We note in particular the continuous amplification of hendecads, both within existing proteins and de novo from previously non-coding sequence, as a powerful mechanism in the genesis of new coiled-coil forms.