Bioinformatics Databases Research Articles

Redesigning error control in cross-linking mass spectrometry enables more robust and sensitive protein-protein interaction studies.

Cross-linking mass spectrometry (XL-MS) allows characterizing protein-protein interactions (PPIs) in native biological systems by capturing cross-links between different proteins (inter-links). However, inter-link identification remains challenging, requiring dedicated data filtering schemes and thorough error control. Here, we benchmark existing data filtering schemes combined with error rate estimation strategies utilizing concatenated target-decoy protein sequence databases. These workflows show shortcomings either in sensitivity (many false negatives) or specificity (many false positives). To ameliorate the limited sensitivity without compromising specificity, we develop an alternative target-decoy search strategy using fused target-decoy databases. Furthermore, we devise a different data filtering scheme that takes the inter-link context of the XL-MS dataset into account. Combining both approaches maintains low error rates and minimizes false negatives, as we show by mathematical simulations, analysis of experimental ground-truth data, and application to various biological datasets. In human cells, inter-link identifications increase by 75% and we confirm their structural accuracy through proteome-wide comparisons to AlphaFold2-derived models. Taken together, target-decoy fusion and context-sensitive data filtering deepen and fine-tune XL-MS-based interactomics.

ProHap enables human proteomic database generation accounting for population diversity.

Amid the advances in genomics, the availability of large reference panels of human haplotypes is key to account for human diversity within and across populations. However, mass spectrometry-based proteomics does not benefit from this information. To address this gap, we introduce ProHap, a Python-based tool that constructs protein sequence databases from phased genotypes of reference panels. ProHap enables researchers to account for haplotype diversity in proteomic searches.

TopDIA: A Software Tool for Top-Down Data-Independent Acquisition Proteomics.

Top-down mass spectrometry is widely used for proteoform identification, characterization, and quantification owing to its ability to analyze intact proteoforms. In the past decade, top-down proteomics has been dominated by top-down data-dependent acquisition mass spectrometry (TD-DDA-MS), and top-down data-independent acquisition mass spectrometry (TD-DIA-MS) has not been well studied. While TD-DIA-MS produces complex multiplexed tandem mass spectrometry (MS/MS) spectra, which are challenging to confidently identify, it selects more precursor ions for MS/MS analysis and has the potential to increase proteoform identifications compared with TD-DDA-MS. Here we present TopDIA, the first software tool for proteoform identification by TD-DIA-MS. It generates demultiplexed pseudo MS/MS spectra from TD-DIA-MS data and then searches the pseudo MS/MS spectra against a protein sequence database for proteoform identification. We compared the performance of TD-DDA-MS and TD-DIA-MS using Escherichia coli K-12 MG1655 cells and demonstrated that TD-DIA-MS with TopDIA increased proteoform and protein identifications compared with TD-DDA-MS.

Effects of energetic compounds on soil microbial communities and functional genes at a typical ammunition demolition site.

High concentrations of energetic compounds such as 2,4,6-trinitrotoluene (TNT), hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX), and octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) in military-contaminated sites pose a serious threat to human health and ecosystems. Better understanding about their effects on microbial diversity and functional genes in soil of ammunition demolition sites is required. In this study, the information of soil microbial community composition was obtained by macrogenome sequencing, and the impacts of energetic compounds on microbial community structure at the level of functional genes and enzymes based on Nr (Non-Redundant Protein Sequence Database), KEGG (Kyoto Encyclopedia of Genes and Genomes), CAZy (Carbohydrate-Active En-zymes Database) and other databases were discussed. The results showed that soil microbial diversity and functional gene abundance decreased significantly with the increase of the concentrations of energetic compounds. Conversely, the relative abundance of Proteobacteria increased significantly, reaching over 80% in the heavily TNT-contaminated area near explosive-waste water pool. Furthermore, functional gene analysis indicated that Proteobacteria had an advantage in degrading energetic compounds, and thus had the potential to improve the soil quality at ammunition demolition sites. This study provides a scientific basis for the future remediation and management of contaminated soils at ammunition demolition sites, as well as for the selection of efficient degraders of energetic compounds.

Construction and characterization of a novel secreted MsC-CAR-T cell in solid tumors

The CD47-SIRPα signaling has been acknowledged as a significant immune checkpoint and CD47 blocking has been proved as a potential therapeutic strategy for the treatment of solid tumor. However, the potential application of CAR-T cells secreted antibody fragment simultaneously in solid tumor is rarely explored. In this study, we searched bioinformatic databases and investigated the characteristics of CD47 in solid tumors. Then we consulted bioinformatic databases to design, optimize and construct a novel MsC-CAR which could target MAGE-A1 and self-secrete CD47-scFv. The engineering T cells containing MsC-CAR were transfected, verified and characterized. The tumor-inhibitory role of MsC-CART cells was further determined in vitro and in vivo. The results showed that MsC-CARs were successfully constructed and MsC1-CARs demonstrated the preferable features of recognizing MAGE-A1 and secreting CD47-scFv. Engineering T cells transfecting with MsC1-CAR (MsC1-CART cells) exerted the prominent tumor-inhibitory effectiveness, both in different cancer cell lines and LUAD xenograft tumors. The present data highlighted that MsC1-CART cells elaborately combined the adoptive cellular immunotherapy and immune checkpoint inhibitor therapy, may represent a new direction for the treatment of MAGE-A1 positive solid tumors.

Prognostic Value and Therapeutic Significance of CCL Chemokines in Gastric Cancer.

Gastric cancer is one of the most common malignant tumours of the gastrointestinal tract, which has a significant negative impact on human health. CCL chemokines play important roles in a variety of tumor microenvironments; nevertheless, gastric cancer has surprisingly limited associations with CCL chemokines. In our study, we comprehensively utilized bioinformatics analysis tools and databases such as cBioPortal, UALCAN, GEPIA, GeneMANIA, STRING, and TRRUST to clarify the clinical significance and biology function of CCL chemokines in gastric cancer. The mRNA expression levels of CCL1/3/4/5/7/8/14/15/18/20/21/22/26 were up-regulated, while the mRNA expression levels of CCL2/11/13/16/17/19/23/24/25/28 were down-regulated. The chemokine significantly associated with the pathological stage of gastric cancer is CCL2/11/19/21. In gastric cancer, the expression level of CCL chemokines was not associated with disease-free survival, but low expression of CCL14 was significantly associated with longer overall survival. Therein, associated with the regulation of CCL chemokines are only 10 transcription factors (RELA, NFKB1, STAT6, IRF3, REL, SPI1, STAT1, STAT3, JUN and SP1). The major biological process and functional enrichment of CCL chemokines are to induce cell-directed migration. These results may indicate that CCL chemokines may be immunotherapeutic targets and promising prognostic biomarkers for gastric cancer.

The Prognostic Value and Clinical Significance of lncRNA SNHG5 Expression in Patients with Multiple Malignancies: A Bioinformatic and Meta-analysis.

Long non-coding RNA small nucleolar RNA host gene 5 (lncRNA SNHG5) has been identified as both a promising target for treatment and a predictor of prognosis in diverse types of cancer. The objective of this study was to assess whether lncRNA SNHG5 expression can be utilized as a prognostic biomarker for human cancer. To ensure a thorough search of the literature for relevant English studies published before July 2023, several databases were searched, including PubMed, Web of Science, ProQuest, Cochrane Library, and Google Scholar. The study evaluated the impact of lncRNA SNHG5 on the overall survival (OS) of cancer by calculating the pooled hazard ratio (HR) and odds ratio (OR) with 95% confidence intervals (CIs). To further confirm the accuracy of the findings, the study investigated the expression profile and prognostic significance of lncRNA SNHG5 through the use of GenomicScape, OncoLnc, Kaplan-Meier plotter, and GEPIA databases. In this study, 995 patients were examined across a total of fourteen original studies. The findings indicated that there was a significant relationship between heightened lncRNA SNHG5 expression and reduced OS, as evidenced by both univariate and multivariate analyses (HR = 1.89; 95% CI, 1.44-2.49; p < 0.001; HR = 3.97; 95% CI, 1.80-8.73; p < 0.001, respectively). Pooled OR analysis showed a significant association between over-expression of lncRNA SNHG5 with advanced histological grade (OR = 0.28; 95% CI, 0.11-0.71; p = 0.007), present lymph node metastasis (LNM; OR = 4.28; 95% CI, 2.47-7.43; p < 0.001), and smoking history (OR = 0.27; 95% CI, 0.15-0.49; p < 0.001). Bioinformatic databases confirmed that elevated SNHG5 expression was significantly linked to poor prognosis in cancer patients, including colorectal cancer (CRC), acute myeloid leukemia (AML), and esophageal adenocarcinoma (ESAD), and a longer OS in patients with uterine corpus endometrial carcinoma (UCEC). These results suggest that lncRNA SNHG5 may serve as an adverse prognostic biomarker in several human cancers. Further investigations are needed to better understand the underlying mechanisms that link lncRNA SNHG5 to multiple malignancies.

Lack of WDFY4 leads to impaired immune response and poor cancer prognosis.

WDFY4 plays an essential role in the immune system by regulating B-cell growth and development and participating in antigen processing during cross-presentation. WDFY4 is closely related to asthma and systemic lupus erythematosus; however, its role in cancer remains unclear. The purpose of this study is to use bioinformatics to determine whether abnormal expression of WDFY4 is a risk factor for cancer and to preliminarily analyze the ways in which WDFY4 affects cancer through experiments. R language packages and bioinformatic database were used to mine the potential carcinogenic effect of WDFY4 and analyze the differential WDFY4 expression in cancer, gene mutations, different tumor prognoses, immune cell infiltration, tumor microenvironment, and DNA methylation correlation. H1975 and A549 cell lines were infected with lentiviruses to overexpress WDFY4, and the effect of WDFY4 on the activity, proliferation, apoptosis, and cell cycle of lung cancer cells was analyzed. WDFY4 was differentially expressed in human tumors in unpaired and paired samples. The differential expression of WDFY4 in unpaired and paired or protein samples from the Clinical Proteome Tumor Analysis Consortium of eight cancers was consistent. WDFY4 methylation was downregulated in 17 cancer types and caused prognostic differences in different directions in some cancers. WDFY4 overexpression significantly inhibited the activity and proliferation of lung cancer cell lines, promoted apoptosis, and caused cell cycle arrest. Differential WDFY4 expression in cancers leads to differences in the prognosis of various cancers. WDFY4 can be an independent prognostic factor for glioma, KIRC, and LUSC.

Mycobacterium smegmatis MraZ Regulates Multiple Genes within and Outside of the dcw Operon during Hypoxia.

Mycobacterium tuberculosis is the most ancient human tuberculosis pathogen and has been the leading cause of death from bacterial infectious diseases throughout human history. According to the World Health Organization Global Tuberculosis Report, in 2022, 7.5 million new tuberculosis cases were identified, marking the highest number of cases since the World Health Organization initiated its worldwide tuberculosis surveillance program in 1995. The 2019 peak was 7.1 million cases, with 5.8 million cases in 2020 and 6.4 million in 2021. The increase in 2022, which may be attributed to the COVID-19 pandemic complicating tuberculosis case tracing, has raised concerns. To better understand the regulation spectrum of Mycobacterium smegmatis mraZ under hypoxia, we performed a transcriptome analysis of M.smegmatis mutant and wild-type strains using Illumina Agilent 5300 sequencing. The study identified 6898 differentially expressed genes, which were annotated with NCBI nonredundant protein sequences, a manually annotated and reviewed protein sequence database, Pfam, Clusters of Orthologous Groups of Proteins, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes. Several mycobacteria transcriptional regulators, virulence genes, membrane transporters, and cell wall biosynthesis genes were annotated. These data serve as a valuable resource for future investigations and may offer insight into the development of drugs to combat M.tuberculosis infection.

Expression levels of some genes in the MAPK pathway (DUSP1, DUSP2, DUSP4, DUSP6 and DUSP10) in eyelid tumor tissue

Abstract Objectives To control mitogen-activated protein kinases (MAPK) signaling pathways involved in the onset and progression of cancer, dual specificity phosphatases (DUSPs/MKP) are essential. This study seeks to detect the correlation between eyelid tumors and the genes DUSPs, known for their influence on MAPK signaling pathways. Additionally, we aim to juxtapose our findings with analyses from various bioinformatics databases. Methods Expression levels of relevant genes in cDNA samples were determined by quantitative PCR method. Open-access databases were used for mutation analysis of relevant genes, mRNA expression changes, and survival analyses, and the STRING database was used for protein-protein interactions. Results It was found that the expression of DUSP1 and DUSP2 showed a significant decrease in the tumor tissue, while a significant increase was detected in the DUSP4 and DUSP6 genes. Additionally, when we compared the study genes with the Cancer Genome Atlas program cancer cohorts, it was found that the DUSP1 and DUSP10 gene expression profiles were downregulated in uveal melanoma compared to other cancer cohorts. Conclusions Significant and obvious changes were observed in the DUSP genes we studied in eyelid tumors. However, the relationship between these genes and cancer must be studied more. Considering that these enzymes are effective in cell proliferation, differentiation, and apoptosis, it would be appropriate to plan comprehensive studies on their interactions with other proteins they interact with in the MAPK pathway.

A pan-cancer study of ADAM9’s immunological function and prognostic value particularly in liver cancer

A pan-cancer analysis summarizing the overall changes in mRNA and protein stability of ADM9, as well as its oncogenic function on immune cell line modulation and checkpoints within the tumor microenvironment (TME), is lacking, despite the fact that ADM9 up-regulation is correlated with the progression of many cancers. Therefore, in this study, we comprehensively analyzed the role of ADAM9 expression and its prognostic value in different cancers to fill this gap. Multiple bioinformatics databases such as Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Clinical Proteomic Tumor Analysis Consortium (CPTAC) were used to evaluate the ADAM9 genetic alternation, phosphorylation, and methylation, and indicated highly positive correlated genes that might play a critical interaction with ADAM9 and their molecular function with GO analysis. We also evaluate the effect of higher ADAM9 with prominent immune modulatory genes and immune infiltration especially in liver cancer pathogenesis stimulates lower NK cell effector functions based on its role in MICA shedding and increasing the Tregs infiltration. Immunohistochemistry (IHC) staining from 90 pathologically verified samples proved the positive correlation between ADAM9 and tumor stages and proved the higher expression of ADAM9 correlated genes (SNX9, APP, TNF, CDH1, ITGAV, MAD2L2) in HCC pathogenesis. In conclusion, this pan-cancer study provides a comprehensive understanding of the prognostic value of ADAM9 in various tumors emphasizing its importance to be considered as an innovative treatment approach, especially in tumor immunity shortly.

CUDASW++4.0: ultra-fast GPU-based Smith–Waterman protein sequence database search

BackgroundThe maximal sensitivity for local pairwise alignment makes the Smith-Waterman algorithm a popular choice for protein sequence database search. However, its quadratic time complexity makes it compute-intensive. Unfortunately, current state-of-the-art software tools are not able to leverage the massively parallel processing capabilities of modern GPUs with close-to-peak performance. This motivates the need for more efficient implementations.ResultsCUDASW++4.0 is a fast software tool for scanning protein sequence databases with the Smith-Waterman algorithm on CUDA-enabled GPUs. Our approach achieves high efficiency for dynamic programming-based alignment computation by minimizing memory accesses and instructions. We provide both efficient matrix tiling, and sequence database partitioning schemes, and exploit next generation floating point arithmetic and novel DPX instructions. This leads to close-to-peak performance on modern GPU generations (Ampere, Ada, Hopper) with throughput rates of up to 1.94 TCUPS, 5.01 TCUPS, 5.71 TCUPS on an A100, L40S, and H100, respectively. Evaluation on the Swiss-Prot, UniRef50, and TrEMBL databases shows that CUDASW++4.0 gains over an order-of-magnitude performance improvements over previous GPU-based approaches (CUDASW++3.0, ADEPT, SW#DB). In addition, our algorithm demonstrates significant speedups over top-performing CPU-based tools (BLASTP, SWIPE, SWIMM2.0), can exploit multi-GPU nodes with linear scaling, and features an impressive energy efficiency of up to 15.7 GCUPS/Watt.ConclusionCUDASW++4.0 changes the standing of GPUs in protein sequence database search with Smith-Waterman alignment by providing close-to-peak performance on modern GPUs. It is freely available at https://github.com/asbschmidt/CUDASW4.

Identification and Validation of circDOCK1/miR-138-5p/GRB7 Axis for Promoting Breast Cancer Progression.

Non-coding RNAs have received increasing attention in human tumors, with RNA interaction networks playing important roles in breast cancer. This study aims to explore novel circular RNAs and their mechanisms of biological function in breast cancer. Six HER2-positive breast cancer tissues and paired normal tissues were obtained for the whole transcriptome RNA sequencing. Differentially expressed (DE) circRNAs, miRNAs and mRNAs were identified and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DERNAs were performed. DECircRNAs- DEmiRNAs- DEmRNAs networks were constructed and further verified by bioinformatics database analyses, luciferase assays and RIP assays. The expression level of circDOCK1 in breast cancer specimens was measured using qRT-PCR. Functional rescue experiments were conducted to explore the role of circDOCK1/miR-138-5p/GRB7 axis in breast cancer cells. The correlation of circDOCK1 expression and clinicopathologic features of 102HER2 positive breast cancer patients was analyzed. A total of 6960 DEmRNAs, 133 DE miRNAs and 1691 DE circRNAs were identified from HER2-positive breast cancer tissues and paracancerous tissues. Enrichment Analysis showed that the differential mRNAs were associated with cell division in biological processes and cell cycle and signaling pathways. GO and KEGG analysis demonstrated that DE circRNAs were mainly enriched in double-strand break repair, positive regulation of transcription by RNA polymerase II, nucleoplasma, nucleus, chromatin binding and protein binding. Forty networks of competing endogenous RNAs (ceRNAs) were constructed and circDOCK1/miR-138-5p/GRB7 axis was verified. Functional experiments revealed that the axis promotes migration and invasion of breast cancer cells. CircDOCK1 expression was elevated in breast cancer patients and correlated with adverse clinicopathologic parameters. Patients with high circDOCK1 level had poor outcomes. A novel circDOCK1/miR-138-5p/GRB7 axis promotes HER2 positive breast cancer metastasis and progression, providing a potential therapeutic target in the treatment of breast cancer.

MiR‑155 promotes an inflammatory response in HaCaT cells via the IRF2BP2/KLF2/NF‑κB pathway in psoriasis.

Psoriasis is a chronic inflammatory skin condition with numerous causes, including genetic, immunological and infectious factors. The course of psoriasis is long and recurrence is common; pathogenesis is not completely understood. However, there is an association between advancement of psoriasis and aberrant microRNA (miR or miRNA)‑155 expression. Through bioinformatics, the present study aimed to analyze the differentially expressed genes and miRNAs in psoriasis and its biological mechanism and function psoriatic inflammation. First of all, differentially expressed genes (DEGs) and miRNAs (DEMs) in patients with psoriasis were identified using GEO2R interactive web application. A psoriasis inflammatory model was established using lipopolysaccharide (LPS)‑treated HaCaT keratinocytes, which were transfected with miR‑155 mimic or inhibitor. Cell Counting Kit‑8 was used for the assessment of cell viability and proliferation, and changes in the cell cycle were examined using flow cytometry. ELISA and reverse transcription‑quantitative PCR (RT‑qPCR) were used to detect the expression levels of the inflammatory factors IL‑1β and IL‑6. The dual‑luciferase reporter assay was used to verify the targeting association between miR‑155‑5p and IFN regulatory factor 2 binding protein 2 (IRF2BP2). To verify the targeting association of miR‑155 and the IRF2BP2/kruppel‑like factor 2 (KLF2)/NF‑κB signaling pathway, expression levels of IRF2BP2, KLF2 and p65 were identified by RT‑qPCR and western blotting. IRF2BP2 levels were also confirmed by immunofluorescence, in conjunction with bioinformatics database analysis. Overexpression of miR‑155 inhibited proliferation of HaCaT cells and increased the number of cells in S phase and decreasing number of cells in G1 and G2 phase. In the LPS‑induced inflammatory state, miR‑155 overexpression heightened the inflammatory response of HaCaT cells while inhibition of miR‑155 lessened it. Suppression of inflammatory cytokine expression by miR‑155‑5p inhibitor was reversed by knockdown of IRF2BP2. miR‑155 was shown to interact with IRF2BP2 to negatively regulate its expression, leading to decreased KLF2 expression and increased p65 expression and secretion of inflammatory factors, intensifying the inflammatory response of HaCaT cells. Therefore, miR‑155 may contribute to development of psoriasis by inducing tissue and cell damage by increasing the inflammatory response of HaCaT cells via the IRF2BP2/KLF2/NF‑κB pathway. In conclusion, the results of the present study offer novel perspectives on the role of miR‑155 in the onset and progression of psoriasis.

Application of computer-aided drug design in drug discovery and development: Updating knowledge

Coronavirus (CoV) diseases are widespread throughout the world and have caused considerable socio-economic disruptions. For this reason, efforts have been made to develop a direct or indirect antiviral drugs against these diseases. However, no specific antiviral drug has yet been approved by the Food and Drug Administration (FDA) for CoV infections. Thus, the challenge in discovering therapeutic molecules against these infections remains pertinent. Computer-aided drug design (CADD) is one of the modern techniques for drug discovery and development. It accelerates the process, minimizes costs, and reduces research time. In this article, we present the three CADD approaches, namely structure-based drug discovery (SBDD), ligand-based drug discovery (LBDD) and high-throughput virtual screening (HTVS). The different methods used in these three approaches CADD, such as molecular modelling, target structure analysis, molecular docking, molecular dynamics simulation, pharmacophore modelling, quantitative structure-activity relationship (QSAR), ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS) are detailed. In addition, the bioinformatics tools and databases commonly used in these different CADD techniques are also described.

Full-length transcriptome assembly of black amur bream (Megalobrama terminalis) as a reference resource.

The genus Megalobrama holds significant economic value in China, with M. terminalis (Black Amur bream) ranking second in production within this group. However, lacking comprehensive genomic and transcriptomic data has impeded research progress. This study aims to fill this gap through an extensive transcriptomic analysis of M. terminalis. We utilized PacBio Isoform Sequencing to generate 558,998 subreads, totaling 45.52 Gb, which yielded 22,141 transcripts after rigorous filtering and clustering. Complementary Illumina short-read sequencing corrected 967,114 errors across these transcripts. Our analysis identified 12,426 non-redundant isoforms, with 11,872 annotated in various databases. Functional annotation indicated 11,841 isoforms matched entries in the NCBI non-redundant protein sequences database. Gene Ontology analysis categorized 10,593 isoforms, revealing strong associations with cellular processes and binding functions. Additionally, 8203 isoforms were mapped to pathways in the Kyoto Encyclopedia of Genes and Genomes, highlighting significant involvement in immune system processes and complement cascades. We notably identified key immune molecules such as alpha-2-macroglobulin and complement component 3, each with multiple isoforms, underscoring their potential roles in the immune response. Our analysis also uncovered 853 alternative splicing events, predominantly involving retained introns, along with 672 transcription factors and 426 long non-coding RNAs. The high-quality reference transcriptome generated in this study provides a valuable resource for comparative genomic studies within the Megalobrama genus, supporting future research to enhance aquaculture stocks.

A study of the clinical significance of mSEPT9 in monitoring recurrence and prognosis in patients with surgically treated colorectal cancer.

To explore the medical significance of methylated septin9 (mSEPT9) in monitoring recurrence and prognostic assessment in individuals with surgically treated colorectal cancer (CRC). To investigate the role of Septin9 in colorectal cancer, we utilized the TIMER2.0 database to analyze its differential expression between tumor tissues and adjacent normal tissues. Colorectal cancer RNA-seq data from the TCGA database was downloaded and curated. The clinical relevance of mSEPT9 in colorectal cancer was explored by examining the correlation between Septin9 methylation levels and clinical characteristics using UALCAN and MethSurv software. Peripheral blood samples were obtained from 130 CRC subjects who underwent surgery for the detection of mSEPT9 and carcinoembryonic antigen (CEA) expression, along with collection of clinicopathological data such as age, gender, tumor site, TNM stage, and tumor differentiation. Patients were followed up for at least 3 years post-surgery until the death or final follow-up dates (31/12/2022). Additionally, peripheral blood samples were collected from 30 colorectal cancer surgery patients for mSEPT9 detection before and 7 days after surgery. Through bioinformatic database analysis, we identified higher expression levels of SEPT9 mRNA in most tumor tissues compared to normal tissues. Similarly, both paired and unpaired CRC tissues exhibited elevated expression of Septin9 when compared to normal tissues. Following GO and KEGG analysis of Septin9 target genes, we discovered their significant associations with ncRNA metabolic processes, ribonucleoprotein complex biogenesis, spliceosomes, and viral carcinogenesis. Furthermore, the overexpression of mSeptin9 was observed in CRC tissues, and it demonstrated a correlation with colon cancer staging and histologic classification. In our clinical sample study, The positive rate of mSEPT9 in CRC patients 7 days after surgery was 43.44% lower than that of preoperative. The differences in TNM stage, tumor differentiation degree, and preoperative CEA expression level between the preoperative mSEPT9 positive and negative groups of CRC were statistically significant (P < 0.05). Recurrence free survival (RFS) and overall survival (OS) were shorter in the preoperative mSEPT9-positive group, meaning preoperative mSEPT9 status was a risk factor for CRC recurrence and prognosis (P < 0.05). The sensitivity, specificity, and AUC value of preoperative mSEPT9 and CEA levels for predicting postoperative recurrence in CRC patients were 88% vs. 72%, 56.19% vs. 55.24%, and 0.721 vs. 0.636 respectively, well the AUC value of the combined prediction of postoperative recurrence was 0.758. The detection of mSEPT9 combined with CEA in preoperative plasma helps predict recurrence in colorectal cancer patients.

Transcriptional factor KLF9 overcomes 5-fluorouracil resistance in breast cancer via PTEN-dependent regulation of aerobic glycolysis

The emergence of resistance to 5-Fluorouracil (5-FU) is a staple in breast cancer chemotherapy. This paper delves into the role of PTEN in breast cancer resistance to 5-FU and examines the underlying molecular pathways. PTEN expression was detected in bioinformatics databases and upstream transcription factors (TFs) were identified. PTEN mRNA and protein levels, aerobic glycolysis proteins, lactate production, glucose consumption, and cell viability were measured. Binding interactions were confirmed, and cell proliferation assessed. In breast cancer cells, PTEN expression was downregulated. PTEN overexpression counteracted 5-FU resistance through the suppression of aerobic glycolysis. KLF9, as a TF upstream of PTEN, enhanced the levels of PTEN. In conclusion, the TF KLF9 inhibits the aerobic glycolysis level of breast cancer cells by up-regulating PTEN expression, thereby reducing their resistance to 5-FU. The discovery of this mechanism provides a new theoretical basis for the treatment of breast cancer.

Construction of Protein Sequence Databases for Metaproteomics: A Review of the Current Tools and Databases.

In metaproteomics studies, constructing a reference protein sequence database that is both comprehensive and not overly large is critical for the peptide identification step. Therefore, the availability of well-curated reference databases and tools for custom database construction is essential to enhance the performance of metaproteomics analyses. In this review, we first provide an overview of metaproteomics by presenting a concise historical background, outlining a typical experimental and bioinformatics workflow, emphasizing the crucial step of constructing a protein sequence database for metaproteomics. We then delve into the current tools available for building such databases, highlighting their individual approaches, utility, and advantages and limitations. Next, we examine existing protein sequence databases, detailing their scope and relevance in metaproteomics research. Then, we provide practical recommendations for constructing protein sequence databases for metaproteomics, along with an overview of the current challenges in this area. We conclude with a discussion of anticipated advancements, emerging trends, and future directions in the construction of protein sequence databases for metaproteomics.

Discovering Novel Proteoforms Using Proteogenomic Workflows Within the Galaxy Bioinformatics Platform.

Proteogenomics is a growing "multi-omics" research area that combines mass spectrometry-based proteomics and high-throughput nucleotide sequencing technologies. Proteogenomics has helped in genomic annotation for organisms whose complete genome sequences became available by using high-throughput DNA sequencing technologies. Apart from genome annotation, this multi-omics approach has also helped researchers confirm expression of variant proteins belonging to unique proteoforms that could have resulted from single-nucleotide polymorphism (SNP), insertion and deletions (Indels), splice isoforms, or other genome or transcriptome variations.A proteogenomic study depends on a multistep informatics workflow, requiring different software at each step. These integrated steps include creating an appropriate protein sequence database, matching spectral data against these sequences, and finally identifying peptide sequences corresponding to novel proteoforms followed by variant classification and functional analysis. The disparate software required for a proteogenomic study is difficult for most researchers to access and use, especially those lacking computational expertise. Furthermore, using them disjointedly can be error-prone as it requires setting up individual parameters for each software. Consequently, reproducibility suffers. Managing output files from each software is an additional challenge. One solution for these challenges in proteogenomics is the open-source Web-based computational platform Galaxy. Its capability to create and manage workflows comprised of disparate software while recording and saving all important parameters promotes both usability and reproducibility. Here, we describe a workflow that can perform proteogenomic analysis on a Galaxy-based platform. This Galaxy workflow facilitates matching of spectral data with a customized protein sequence database, identifying novel protein variants, assessing quality of results, and classifying variants along with visualization against the genome.